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Java Titles & abstracts 2013-2014
Java Titles & abstracts 2013-2014
Java Titles & abstracts 2013-2014
Java Titles & abstracts 2013-2014
Java Titles & abstracts 2013-2014
Java Titles & abstracts 2013-2014
Java Titles & abstracts 2013-2014
Java Titles & abstracts 2013-2014
Java Titles & abstracts 2013-2014
Java Titles & abstracts 2013-2014
Java Titles & abstracts 2013-2014
Java Titles & abstracts 2013-2014
Java Titles & abstracts 2013-2014
Java Titles & abstracts 2013-2014
Java Titles & abstracts 2013-2014
Java Titles & abstracts 2013-2014
Java Titles & abstracts 2013-2014
Java Titles & abstracts 2013-2014
Java Titles & abstracts 2013-2014
Java Titles & abstracts 2013-2014
Java Titles & abstracts 2013-2014
Java Titles & abstracts 2013-2014
Java Titles & abstracts 2013-2014
Java Titles & abstracts 2013-2014
Java Titles & abstracts 2013-2014
Java Titles & abstracts 2013-2014
Java Titles & abstracts 2013-2014
Java Titles & abstracts 2013-2014
Java Titles & abstracts 2013-2014
Java Titles & abstracts 2013-2014
Java Titles & abstracts 2013-2014
Java Titles & abstracts 2013-2014
Java Titles & abstracts 2013-2014
Java Titles & abstracts 2013-2014
Java Titles & abstracts 2013-2014
Java Titles & abstracts 2013-2014
Java Titles & abstracts 2013-2014
Java Titles & abstracts 2013-2014
Java Titles & abstracts 2013-2014
Java Titles & abstracts 2013-2014
Java Titles & abstracts 2013-2014
Java Titles & abstracts 2013-2014
Java Titles & abstracts 2013-2014
Java Titles & abstracts 2013-2014
Java Titles & abstracts 2013-2014
Java Titles & abstracts 2013-2014
Java Titles & abstracts 2013-2014
Java Titles & abstracts 2013-2014
Java Titles & abstracts 2013-2014
Java Titles & abstracts 2013-2014
Java Titles & abstracts 2013-2014
Java Titles & abstracts 2013-2014
Java Titles & abstracts 2013-2014
Java Titles & abstracts 2013-2014
Java Titles & abstracts 2013-2014
Java Titles & abstracts 2013-2014
Java Titles & abstracts 2013-2014
Java Titles & abstracts 2013-2014
Java Titles & abstracts 2013-2014
Java Titles & abstracts 2013-2014
Java Titles & abstracts 2013-2014
Java Titles & abstracts 2013-2014
Java Titles & abstracts 2013-2014
Java Titles & abstracts 2013-2014
Java Titles & abstracts 2013-2014
Java Titles & abstracts 2013-2014
Java Titles & abstracts 2013-2014
Java Titles & abstracts 2013-2014
Java Titles & abstracts 2013-2014
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Java Titles & abstracts 2013-2014

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  • 1. IEEE- Project Title 2013 1 33,Meenakshi Sundaram Building, Sivaji st, (Near Tnagar Bus Terminus),TNagar Chennai-17, Ph: 044-42070551 Mobile: 9025439777/ www.sybiantechnologies.com / sybianprojects@gmail.com JAVA BIO MEDICAL / MEDICAL IMAGING 1. Simultaneously Identifying All True Vessels From Segmented Retinal Images ABSTRACT: Measurements of retinal blood vessel morphology have been shown to be related to the risk of cardiovascular diseases. The wrong identification of vessels may result in a large variation of these measurements, leading to a wrong clinical diagnosis. In this paper, we address the problem of automatically identifying true vessels as a postprocessing step to vascular structure segmentation. We model the segmented vascular structure as a vessel segment graph and formulate the problem of identifying vessels as one of finding the optimal forest in the graph given a set of constraints. We design a method to solve this optimization problem and evaluate it on a large real-world dataset of 2446 retinal images. Experiment results are analyzed with respect to actual measurements of vessel morphology. The results show that the proposed approach is able to achieve 98.9% pixel precision and 98.7% recall of the true vessels for clean segmented retinal images, and remains robust even when the segmented image is noisy.
  • 2. IEEE- Project Title 2013 2 33,Meenakshi Sundaram Building, Sivaji st, (Near Tnagar Bus Terminus),TNagar Chennai-17, Ph: 044-42070551 Mobile: 9025439777/ www.sybiantechnologies.com / sybianprojects@gmail.com 2. A modified fuzzy c-means algorithm for bias field estimation and segmentation of MRI data ABSTRACT: We present a novel algorithm for fuzzy segmentation of magnetic resonance imaging (MRI) data and estimation of intensity inhomogeneities using fuzzy logic. MRI intensity inhomogeneities can be attributed to imperfections in the radio- frequency coils or to problems associated with the acquisition sequences. The result is a slowly varying shading artifact over the image that can produce errors with conventional intensity-based classification. Our algorithm is formulated by modifying the objective function of the standard fuzzy c-means (FCM) algorithm to compensate for such inhomogeneities and to allow the labeling of a pixel (voxel) to be influenced by the labels in its immediate neighborhood. The neighborhood effect acts as a regularizer and biases the solution toward piecewise-homogeneous labelings. Such a regularization is useful in segmenting scans corrupted by salt and pepper noise. Experimental results on both synthetic images and MR data are given to demonstrate the effectiveness and efficiency of the proposed algorithm. 3. Feature-Based Image Patch Approximation for Lung Tissue Classification ABSTRACT: In this paper, we propose a new classification method for five categories of lung tissues in high-resolution computed tomography (HRCT) images, with feature-based image patch approximation. We design two new feature descriptors
  • 3. IEEE- Project Title 2013 3 33,Meenakshi Sundaram Building, Sivaji st, (Near Tnagar Bus Terminus),TNagar Chennai-17, Ph: 044-42070551 Mobile: 9025439777/ www.sybiantechnologies.com / sybianprojects@gmail.com for higher feature descriptiveness, namely the rotation-invariant Gabor-local binary patterns (RGLBP) texture descriptor and multi-coordinate histogram of oriented gradients (MCHOG) gradient descriptor. Together with intensity features, each image patch is then labeled based on its feature approximation from reference image patches. And a new patch-adaptive sparse approximation (PASA) method is designed with the following main components: minimum discrepancy criteria for sparse-based classification, patch-specific adaptation for discriminative approximation, and feature-space weighting for distance computation. The patch- wise labelings are then accumulated as probabilistic estimations for region-level classification. The proposed method is evaluated on a publicly available ILD database, showing encouraging performance improvements over the state-of-the- arts. 4. Automatic Segmentation of the Pulmonary Lobes From Chest CT Scans Based on Fissures, Vessels, and Bronchi ABSTRACT: Segmentation of the pulmonary lobes is relevant in clinical practice and particularly challenging for cases with severe diseases or incomplete fissures. In this work, an automated segmentation approach is presented that performs a marker-based watershed transformation on computed tomography (CT) scans to subdivide the lungs into lobes. A cost image for the watershed transformation is computed by combining information from fissures, bronchi, and pulmonary vessels. The lobar markers are calculated by an analysis of the automatically labeled bronchial tree. By integration of information from several anatomical
  • 4. IEEE- Project Title 2013 4 33,Meenakshi Sundaram Building, Sivaji st, (Near Tnagar Bus Terminus),TNagar Chennai-17, Ph: 044-42070551 Mobile: 9025439777/ www.sybiantechnologies.com / sybianprojects@gmail.com structures the segmentation is made robust against incomplete fissures. For evaluation the method was compared to a recently published method on 20 CT scans with no or mild disease. The average distances to the reference segmentation were 0.69, 0.67, and 1.21 mm for the left major, right major, and right minor fissure, respectively. In addition the results were submitted to LOLA11, an international lung lobe segmentation challenge with publically available data including cases with severe diseases. The average distances to the reference for the 55 CT scans provided by LOLA11 were 0.98, 3.97, and 3.09 mm for the left major, right major, and right minor fissure. Moreover, an analysis of the relation between segmentation quality and fissure completeness showed that the method is robust against incomplete fissures.
  • 5. IEEE- Project Title 2013 5 33,Meenakshi Sundaram Building, Sivaji st, (Near Tnagar Bus Terminus),TNagar Chennai-17, Ph: 044-42070551 Mobile: 9025439777/ www.sybiantechnologies.com / sybianprojects@gmail.com CLOUD COMPUTING 1. Efficient Resource Mapping Framework over Networked Clouds via Iterated Local Search-Based Request Partitioning ABSTRACT: The cloud represents a computing paradigm where shared configurable resources are provided as a service over the Internet. Adding intra- or intercloud communication resources to the resource mix leads to a networked cloud computing environment. Following the cloud infrastructure as a Service paradigm and in order to create a flexible management framework, it is of paramount importance to address efficiently the resource mapping problem within this context. To deal with the inherent complexity and scalability issue of the resource mapping problem across different administrative domains, in this paper a hierarchical framework is described. First, a novel request partitioning approach based on Iterated Local Search is introduced that facilitates the cost-efficient and online splitting of user requests among eligible cloud service providers (CPs) within a networked cloud environment. Following and capitalizing on the outcome of the request partitioning phase, the embedding phase-where the actual mapping of requested virtual to physical resources is performed can be realized through the use of a distributed intracloud resource mapping approach that allows for efficient and balanced allocation of cloud resources. Finally, a thorough evaluation of the proposed overall framework on a simulated networked cloud environment is provided and critically compared against an exact request partitioning solution as well as another common intradomain virtual resource embedding solution.
  • 6. IEEE- Project Title 2013 6 33,Meenakshi Sundaram Building, Sivaji st, (Near Tnagar Bus Terminus),TNagar Chennai-17, Ph: 044-42070551 Mobile: 9025439777/ www.sybiantechnologies.com / sybianprojects@gmail.com 2. Hessian Regularized Support Vector Machines for Mobile Image Annotation on the Cloud ABSTRACT: With the rapid development of the cloud computing and mobile service, users expect a better experience through multimedia computing, such as automatic or semi-automatic personal image and video organization and intelligent user interface. These functions heavily depend on the success of image understanding, and thus large-scale image annotation has received intensive attention in recent years. The collaboration between mobile and cloud opens a new avenue for image annotation, because the heavy computation can be transferred to the cloud for immediately responding user actions. In this paper, we present a scheme for image annotation on the cloud, which transmits mobile images compressed by Hamming compressed sensing to the cloud and conducts semantic annotation through a novel Hessian regularized support vector machine on the cloud. We carefully explained the rationality of Hessian regularization for encoding the local geometry of the compact support of the marginal distribution and proved that Hessian regularized support vector machine in the reproducing kernel Hilbert space is equivalent to conduct Hessian regularized support vector machine in the space spanned by the principal components of the kernel principal component analysis. We conducted experiments on the PASCAL VOC'07 dataset and demonstrated the effectiveness of Hessian regularized support vector machine for large-scale image annotation.
  • 7. IEEE- Project Title 2013 7 33,Meenakshi Sundaram Building, Sivaji st, (Near Tnagar Bus Terminus),TNagar Chennai-17, Ph: 044-42070551 Mobile: 9025439777/ www.sybiantechnologies.com / sybianprojects@gmail.com 3. An Adaptive Cloud Downloading Service ABSTRACT: Video content downloading using the P2P approach is scalable, but does not always give good performance. Recently, subscription-based premium services have emerged, referred to as cloud downloading. In this service, the cloud storage and server caches user-interested content and updates the cache based on user downloading requests. If a requested video is not in the cache, the request is held in a waiting state until the cache is updated. We call this design server mode. An alternative design is to let the cloud server serve all downloading requests as soon as they arrive, behaving as a helper peer. We call this design helper mode. Our model and analysis show that both these designs are useful for certain operating regimes. The helper mode is good at handling a high request rate, while the server mode is good at scaling with video population size. We design an adaptive algorithm (AMS) to select the service mode automatically. Intuitively, AMS switches service mode from server mode to helper mode when too many peers request blocked movies, and vice versa. The ability of AMS to achieve good performance in different operating regimes is validated by simulation . 4. A Highly Practical Approach toward Achieving Minimum Data Sets Storage Cost in the Cloud ABSTRACT: Massive computation power and storage capacity of cloud computing systems allow scientists to deploy computation and data intensive applications
  • 8. IEEE- Project Title 2013 8 33,Meenakshi Sundaram Building, Sivaji st, (Near Tnagar Bus Terminus),TNagar Chennai-17, Ph: 044-42070551 Mobile: 9025439777/ www.sybiantechnologies.com / sybianprojects@gmail.com without infrastructure investment, where large application data sets can be stored in the cloud. Based on the pay-as-you-go model, storage strategies and benchmarking approaches have been developed for cost-effectively storing large volume of generated application data sets in the cloud. However, they are either insufficiently cost-effective for the storage or impractical to be used at runtime. In this paper, toward achieving the minimum cost benchmark, we propose a novel highly cost-effective and practical storage strategy that can automatically decide whether a generated data set should be stored or not at runtime in the cloud. The main focus of this strategy is the local-optimization for the tradeoff between computation and storage, while secondarily also taking users' (optional) preferences on storage into consideration. Both theoretical analysis and simulations conducted on general (random) data sets as well as specific real world applications with Amazon's cost model show that the cost-effectiveness of our strategy is close to or even the same as the minimum cost benchmark, and the efficiency is very high for practical runtime utilization in the cloud. 5. AMES-Cloud: A Framework of Adaptive Mobile Video Streaming and Efficient Social Video Sharing in the Clouds ABSTRACT: While demands on video traffic over mobile networks have been souring, the wireless link capacity cannot keep up with the traffic demand. The gap between the traffic demand and the link capacity, along with time-varying link conditions, results in poor service quality of video streaming over mobile networks such as long buffering time and intermittent disruptions. Leveraging the cloud computing
  • 9. IEEE- Project Title 2013 9 33,Meenakshi Sundaram Building, Sivaji st, (Near Tnagar Bus Terminus),TNagar Chennai-17, Ph: 044-42070551 Mobile: 9025439777/ www.sybiantechnologies.com / sybianprojects@gmail.com technology, we propose a new mobile video streaming framework, dubbed AMES- Cloud, which has two main parts: adaptive mobile video streaming (AMoV) and efficient social video sharing (ESoV). AMoV and ESoV construct a private agent to provide video streaming services efficiently for each mobile user. For a given user, AMoV lets her private agent adaptively adjust her streaming flow with a scalable video coding technique based on the feedback of link quality. Likewise, ESoV monitors the social network interactions among mobile users, and their private agents try to prefetch video content in advance. We implement a prototype of the AMES-Cloud framework to demonstrate its performance. It is shown that the private agents in the clouds can effectively provide the adaptive streaming, and perform video sharing (i.e., prefetching) based on the social network analysis. 6. Efficient Resource Provisioning and Rate Selection for Stream Mining in a Community Cloud ABSTRACT: Real-time stream mining such as surveillance and personal health monitoring, which involves sophisticated mathematical operations, is computation- intensive and prohibitive for mobile devices due to the hardware/computation constraints. To satisfy the growing demand for stream mining in mobile networks, we propose to employ a cloud-based stream mining system in which the mobile devices send via wireless links unclassified media streams to the cloud for classification. We aim at minimizing the classification-energy cost, defined as an affine combination of classification cost and energy consumption at the cloud, subject to an average stream mining delay constraint (which is important in real-
  • 10. IEEE- Project Title 2013 10 33,Meenakshi Sundaram Building, Sivaji st, (Near Tnagar Bus Terminus),TNagar Chennai-17, Ph: 044-42070551 Mobile: 9025439777/ www.sybiantechnologies.com / sybianprojects@gmail.com time applications). To address the challenge of time-varying wireless channel conditions without a priori information about the channel statistics, we develop an online algorithm in which the cloud operator can dynamically adjust its resource provisioning on the fly and the mobile devices can adapt their transmission rates to the instantaneous channel conditions. It is proved that, at the expense of increasing the average stream mining delay, the online algorithm achieves a classification- energy cost that can be pushed arbitrarily close to the minimum cost achieved by the optimal offline algorithm. Extensive simulations are conducted to validate the analysis. 7. ptimal Multiserver Configuration for Profit Maximization in Cloud Computing ABSTRACT: As cloud computing becomes more and more popular, understanding the economics of cloud computing becomes critically important. To maximize the profit, a service provider should understand both service charges and business costs, and how they are determined by the characteristics of the applications and the configuration of a multiserver system. The problem of optimal multiserver configuration for profit maximization in a cloud computing environment is studied. Our pricing model takes such factors into considerations as the amount of a service, the workload of an application environment, the configuration of a multiserver system, the service-level agreement, the satisfaction of a consumer, the quality of a service, the penalty of a low-quality service, the cost of renting, the cost of energy consumption, and a service provider's margin and profit. Our
  • 11. IEEE- Project Title 2013 11 33,Meenakshi Sundaram Building, Sivaji st, (Near Tnagar Bus Terminus),TNagar Chennai-17, Ph: 044-42070551 Mobile: 9025439777/ www.sybiantechnologies.com / sybianprojects@gmail.com approach is to treat a multiserver system as an M/M/m queuing model, such that our optimization problem can be formulated and solved analytically. Two server speed and power consumption models are considered, namely, the idle-speed model and the constant-speed model. The probability density function of the waiting time of a newly arrived service request is derived. The expected service charge to a service request is calculated. The expected net business gain in one unit of time is obtained. Numerical calculations of the optimal server size and the optimal server speed are demonstrated. 8. CAM: Cloud-Assisted Privacy Preserving Mobile Health Monitoring ABSTRACT: Cloud-assisted mobile health (mHealth) monitoring, which applies the prevailing mobile communications and cloud computing technologies to provide feedback decision support, has been considered as a revolutionary approach to improving the quality of healthcare service while lowering the healthcare cost. Unfortunately, it also poses a serious risk on both clients' privacy and intellectual property of monitoring service providers, which could deter the wide adoption of mHealth technology. This paper is to address this important problem and design a cloud-assisted privacy preserving mobile health monitoring system to protect the privacy of the involved parties and their data. Moreover, the outsourcing decryption technique and a newly proposed key private proxy reencryption are adapted to shift the computational complexity of the involved parties to the cloud without compromising clients' privacy and service providers' intellectual property.
  • 12. IEEE- Project Title 2013 12 33,Meenakshi Sundaram Building, Sivaji st, (Near Tnagar Bus Terminus),TNagar Chennai-17, Ph: 044-42070551 Mobile: 9025439777/ www.sybiantechnologies.com / sybianprojects@gmail.com Finally, our security and performance analysis demonstrates the effectiveness of our proposed design. 9. Cloud-Based Image Coding for Mobile Devices—Toward Thousands to One Compression ABSTRACT: Current image coding schemes make it hard to utilize external images for compression even if highly correlated images can be found in the cloud. To solve this problem, we propose a method of cloud-based image coding that is different from current image coding even on the ground. It no longer compresses images pixel by pixel and instead tries to describe images and reconstruct them from a large-scale image database via the descriptions. First, we describe an input image based on its down-sampled version and local feature descriptors. The descriptors are used to retrieve highly correlated images in the cloud and identify corresponding patches. The down-sampled image serves as a target to stitch retrieved image patches together. Second, the down-sampled image is compressed using current image coding. The feature vectors of local descriptors are predicted by the corresponding vectors extracted in the decoded down-sampled image. The predicted residual vectors are compressed by transform, quantization, and entropy coding. The experimental results show that the visual quality of reconstructed images is significantly better than that of intra-frame coding in HEVC and JPEG at thousands to one compression .
  • 13. IEEE- Project Title 2013 13 33,Meenakshi Sundaram Building, Sivaji st, (Near Tnagar Bus Terminus),TNagar Chennai-17, Ph: 044-42070551 Mobile: 9025439777/ www.sybiantechnologies.com / sybianprojects@gmail.com 10.Optimizing Cloud Resources for Delivering IPTV Services Through Virtualization ABSTRACT: Virtualized cloud-based services can take advantage of statistical multiplexing across applications to yield significant cost savings. However, achieving similar savings with real-time services can be a challenge. In this paper, we seek to lower a provider's costs for real-time IPTV services through a virtualized IPTV architecture and through intelligent time-shifting of selected services. Using Live TV and Video-on-Demand (VoD) as examples, we show that we can take advantage of the different deadlines associated with each service to effectively multiplex these services. We provide a generalized framework for computing the amount of resources needed to support multiple services, without missing the deadline for any service. We construct the problem as an optimization formulation that uses a generic cost function. We consider multiple forms for the cost function (e.g., maximum, convex and concave functions) reflecting the cost of providing the service. The solution to this formulation gives the number of servers needed at different time instants to support these services. We implement a simple mechanism for time-shifting scheduled jobs in a simulator and study the reduction in server load using real traces from an operational IPTV network. Our results show that we are able to reduce the load by ~24%(compared to a possible ~31.3% as predicted by the optimization framework).
  • 14. IEEE- Project Title 2013 14 33,Meenakshi Sundaram Building, Sivaji st, (Near Tnagar Bus Terminus),TNagar Chennai-17, Ph: 044-42070551 Mobile: 9025439777/ www.sybiantechnologies.com / sybianprojects@gmail.com 11.A Network and Device Aware QoS Approach for Cloud-Based Mobile Streaming ABSTRACT: Cloud multimedia services provide an efficient, flexible, and scalable data processing method and offer a solution for the user demands of high quality and diversified multimedia. As intelligent mobile phones and wireless networks become more and more popular, network services for users are no longer limited to the home. Multimedia information can be obtained easily using mobile devices, allowing users to enjoy ubiquitous network services. Considering the limited bandwidth available for mobile streaming and different device requirements, this study presented a network and device-aware Quality of Service (QoS) approach that provides multimedia data suitable for a terminal unit environment via interactive mobile streaming services, further considering the overall network environment and adjusting the interactive transmission frequency and the dynamic multimedia transcoding, to avoid the waste of bandwidth and terminal power. Finally, this study realized a prototype of this architecture to validate the feasibility of the proposed method. According to the experiment, this method could provide efficient self-adaptive multimedia streaming services for varying bandwidth environments.
  • 15. IEEE- Project Title 2013 15 33,Meenakshi Sundaram Building, Sivaji st, (Near Tnagar Bus Terminus),TNagar Chennai-17, Ph: 044-42070551 Mobile: 9025439777/ www.sybiantechnologies.com / sybianprojects@gmail.com 12.Anchor: A Versatile and Efficient Framework for Resource Management in the Cloud ABSTRACT: We present Anchor, a general resource management architecture that uses the stable matching framework to decouple policies from mechanisms when mapping virtual machines to physical servers. In Anchor, clients and operators are able to express a variety of distinct resource management policies as they deem fit, and these policies are captured as preferences in the stable matching framework. The highlight of Anchor is a new many-to-one stable matching theory that efficiently matches VMs with heterogeneous resource needs to servers, using both offline and online algorithms. Our theoretical analyses show the convergence and optimality of the algorithm. Our experiments with a prototype implementation on a 20-node server cluster, as well as large-scale simulations based on real-world workload traces, demonstrate that the architecture is able to realize a diverse set of policy objectives with good performance and practicality. 13.Load Rebalancing for Distributed File Systems in Clouds ABSTRACT: Distributed file systems are key building blocks for cloud computing applications based on the MapReduce programming paradigm. In such file systems, nodes simultaneously serve computing and storage functions; a file is partitioned into a number of chunks allocated in distinct nodes so that MapReduce tasks can be performed in parallel over the nodes. However, in a cloud computing
  • 16. IEEE- Project Title 2013 16 33,Meenakshi Sundaram Building, Sivaji st, (Near Tnagar Bus Terminus),TNagar Chennai-17, Ph: 044-42070551 Mobile: 9025439777/ www.sybiantechnologies.com / sybianprojects@gmail.com environment, failure is the norm, and nodes may be upgraded, replaced, and added in the system. Files can also be dynamically created, deleted, and appended. This results in load imbalance in a distributed file system; that is, the file chunks are not distributed as uniformly as possible among the nodes. Emerging distributed file systems in production systems strongly depend on a central node for chunk reallocation. This dependence is clearly inadequate in a large-scale, failure-prone environment because the central load balancer is put under considerable workload that is linearly scaled with the system size, and may thus become the performance bottleneck and the single point of failure. In this paper, a fully distributed load rebalancing algorithm is presented to cope with the load imbalance problem. Our algorithm is compared against a centralized approach in a production system and a competing distributed solution presented in the literature. The simulation results indicate that our proposal is comparable with the existing centralized approach and considerably outperforms the prior distributed algorithm in terms of load imbalance factor, movement cost, and algorithmic overhead. The performance of our proposal implemented in the Hadoop distributed file system is further investigated in a cluster environment. 14.Towards Trustworthy Resource Scheduling in Clouds ABSTRACT: Managing the allocation of cloud virtual machines at physical resources is a key requirement for the success of clouds. Current implementations of cloud schedulers do not consider the entire cloud infrastructure neither do they consider the overall user and infrastructure properties. This results in major security,
  • 17. IEEE- Project Title 2013 17 33,Meenakshi Sundaram Building, Sivaji st, (Near Tnagar Bus Terminus),TNagar Chennai-17, Ph: 044-42070551 Mobile: 9025439777/ www.sybiantechnologies.com / sybianprojects@gmail.com privacy, and resilience concerns. In this paper, we propose a novel cloud scheduler which considers both user requirements and infrastructure properties. We focus on assuring users that their virtual resources are hosted using physical resources that match their requirements without getting users involved with understanding the details of the cloud infrastructure. As a proof-of-concept, we present our prototype which is built on OpenStack. The provided prototype implements the proposed cloud scheduler. It also provides an implementation of our previous work on cloud trust management which provides the scheduler with input about the trust status of the cloud infrastructure.
  • 18. IEEE- Project Title 2013 18 33,Meenakshi Sundaram Building, Sivaji st, (Near Tnagar Bus Terminus),TNagar Chennai-17, Ph: 044-42070551 Mobile: 9025439777/ www.sybiantechnologies.com / sybianprojects@gmail.com DATA MINING 1. Anonymization of Centralized and Distributed Social Networks by Sequential Clustering ABSTRACT: We study the problem of privacy-preservation in social networks. We consider the distributed setting in which the network data is split between several data holders. The goal is to arrive at an anonymized view of the unified network without revealing to any of the data holders information about links between nodes that are controlled by other data holders. To that end, we start with the centralized setting and offer two variants of an anonymization algorithm which is based on sequential clustering (Sq). Our algorithms significantly outperform the SaNGreeA algorithm due to Campan and Truta which is the leading algorithm for achieving anonymity in networks by means of clustering. We then devise secure distributed versions of our algorithms. To the best of our knowledge, this is the first study of privacy preservation in distributed social networks. We conclude by outlining future research proposals in that direction. 2. A Proxy-Based Approach to Continuous Location-Based Spatial Queries in Mobile Environments ABSTRACT: Caching valid regions of spatial queries at mobile clients is effective in reducing the number of queries submitted by mobile clients and query load on the
  • 19. IEEE- Project Title 2013 19 33,Meenakshi Sundaram Building, Sivaji st, (Near Tnagar Bus Terminus),TNagar Chennai-17, Ph: 044-42070551 Mobile: 9025439777/ www.sybiantechnologies.com / sybianprojects@gmail.com server. However, mobile clients suffer from longer waiting time for the server to compute valid regions. We propose in this paper a proxy-based approach to continuous nearest-neighbor (NN) and window queries. The proxy creates estimated valid regions (EVRs) for mobile clients by exploiting spatial and temporal locality of spatial queries. For NN queries, we devise two new algorithms to accelerate EVR growth, leading the proxy to build effective EVRs even when the cache size is small. On the other hand, we propose to represent the EVRs of window queries in the form of vectors, called estimated window vectors (EWVs), to achieve larger estimated valid regions. This novel representation and the associated creation algorithm result in more effective EVRs of window queries. In addition, due to the distinct characteristics, we use separate index structures, namely EVR-tree and grid index, for NN queries and window queries, respectively. To further increase efficiency, we develop algorithms to exploit the results of NN queries to aid grid index growth, benefiting EWV creation of window queries. Similarly, the grid index is utilized to support NN query answering and EVR updating. We conduct several experiments for performance evaluation. The experimental results show that the proposed approach significantly outperforms the existing proxy-based approaches. 3. Efficient Algorithms for Mining High Utility Itemsets from Transactional Databases ABSTRACT: Mining high utility itemsets from a transactional database refers to the discovery of itemsets with high utility like profits. Although a number of relevant
  • 20. IEEE- Project Title 2013 20 33,Meenakshi Sundaram Building, Sivaji st, (Near Tnagar Bus Terminus),TNagar Chennai-17, Ph: 044-42070551 Mobile: 9025439777/ www.sybiantechnologies.com / sybianprojects@gmail.com algorithms have been proposed in recent years, they incur the problem of producing a large number of candidate itemsets for high utility itemsets. Such a large number of candidate itemsets degrades the mining performance in terms of execution time and space requirement. The situation may become worse when the database contains lots of long transactions or long high utility itemsets. In this paper, we propose two algorithms, namely utility pattern growth (UP-Growth) and UP-Growth+, for mining high utility itemsets with a set of effective strategies for pruning candidate itemsets. The information of high utility itemsets is maintained in a tree-based data structure named utility pattern tree (UP-Tree) such that candidate itemsets can be generated efficiently with only two scans of database. The performance of UP-Growth and UP-Growth+ is compared with the state-of- the-art algorithms on many types of both real and synthetic data sets. Experimental results show that the proposed algorithms, especially UP-Growth+, not only reduce the number of candidates effectively but also outperform other algorithms substantially in terms of runtime, especially when databases contain lots of long transactions. 4. Multiparty Access Control for Online Social Networks: Model and Mechanisms ABSTRACT: Online social networks (OSNs) have experienced tremendous growth in recent years and become a de facto portal for hundreds of millions of Internet users. These OSNs offer attractive means for digital social interactions and information sharing, but also raise a number of security and privacy issues. While
  • 21. IEEE- Project Title 2013 21 33,Meenakshi Sundaram Building, Sivaji st, (Near Tnagar Bus Terminus),TNagar Chennai-17, Ph: 044-42070551 Mobile: 9025439777/ www.sybiantechnologies.com / sybianprojects@gmail.com OSNs allow users to restrict access to shared data, they currently do not provide any mechanism to enforce privacy concerns over data associated with multiple users. To this end, we propose an approach to enable the protection of shared data associated with multiple users in OSNs. We formulate an access control model to capture the essence of multiparty authorization requirements, along with a multiparty policy specification scheme and a policy enforcement mechanism. Besides, we present a logical representation of our access control model that allows us to leverage the features of existing logic solvers to perform various analysis tasks on our model. We also discuss a proof-of-concept prototype of our approach as part of an application in Facebook and provide usability study and system evaluation of our method. 5. Discovering Characterizations of the Behavior of Anomalous Subpopulations ABSTRACT: We consider the problem of discovering attributes, or properties, accounting for the a priori stated abnormality of a group of anomalous individuals (the outliers) with respect to an overall given population (the inliers). To this aim, we introduce the notion of exceptional property and define the concept of exceptionality score, which measures the significance of a property. In particular, in order to single out exceptional properties, we resort to a form of minimum distance estimation for evaluating the badness of fit of the values assumed by the outliers compared to the probability distribution associated with the values assumed by the inliers. Suitable exceptionality scores are introduced for both
  • 22. IEEE- Project Title 2013 22 33,Meenakshi Sundaram Building, Sivaji st, (Near Tnagar Bus Terminus),TNagar Chennai-17, Ph: 044-42070551 Mobile: 9025439777/ www.sybiantechnologies.com / sybianprojects@gmail.com numeric and categorical attributes. These scores are, both from the analytical and the empirical point of view, designed to be effective for small samples, as it is the case for outliers. We present an algorithm, called EXPREX, for efficiently discovering exceptional properties. The algorithm is able to reduce the needed computational effort by not exploring many irrelevant numerical intervals and by exploiting suitable pruning rules. The experimental results confirm that our technique is able to provide knowledge characterizing outliers in a natural manner. 6. On Identifying Critical Nuggets of Information during Classification Tasks ABSTRACT: In large databases, there may exist critical nuggets-small collections of records or instances that contain domain-specific important information. This information can be used for future decision making such as labeling of critical, unlabeled data records and improving classification results by reducing false positive and false negative errors. This work introduces the idea of critical nuggets, proposes an innovative domain-independent method to measure criticality, suggests a heuristic to reduce the search space for finding critical nuggets, and isolates and validates critical nuggets from some real-world data sets. It seems that only a few subsets may qualify to be critical nuggets, underlying the importance of finding them. The proposed methodology can detect them. This work also identifies certain properties of critical nuggets and provides experimental validation of the properties. Experimental results also helped validate that critical nuggets can assist in improving classification accuracies in real-world data sets.
  • 23. IEEE- Project Title 2013 23 33,Meenakshi Sundaram Building, Sivaji st, (Near Tnagar Bus Terminus),TNagar Chennai-17, Ph: 044-42070551 Mobile: 9025439777/ www.sybiantechnologies.com / sybianprojects@gmail.com 7. A Predictive-Reactive Method for Improving the Robustness of Real- Time Data Services ABSTRACT: Supporting timely data services using fresh data in data-intensive real-time applications, such as e-commerce and transportation management is desirable but challenging, since the workload may vary dynamically. To control the data service delay to be below the specified threshold, we develop a predictive as well as reactive method for database admission control. The predictive method derives the workload bound for admission control in a predictive manner, making no statistical or queuing-theoretic assumptions about workloads. Also, our reactive scheme based on formal feedback control theory continuously adjusts the database load bound to support the delay threshold. By adapting the load bound in a proactive fashion, we attempt to avoid severe overload conditions and excessive delays before they occur. Also, the feedback control scheme enhances the timeliness by compensating for potential prediction errors due to dynamic workloads. Hence, the predictive and reactive methods complement each other, enhancing the robustness of real-time data services as a whole. We implement the integrated approach and several baselines in an open-source database. Compared to the tested open-loop, feedback-only, and statistical prediction + feedback baselines representing the state of the art, our integrated method significantly improves the average/transient delay and real-time data service throughput.
  • 24. IEEE- Project Title 2013 24 33,Meenakshi Sundaram Building, Sivaji st, (Near Tnagar Bus Terminus),TNagar Chennai-17, Ph: 044-42070551 Mobile: 9025439777/ www.sybiantechnologies.com / sybianprojects@gmail.com 8. Tweet Analysis for Real-Time Event Detection and Earthquake Reporting System Development ABTSRACT: Twitter has received much attention recently. An important characteristic of Twitter is its real-time nature. We investigate the real-time interaction of events such as earthquakes in Twitter and propose an algorithm to monitor tweets and to detect a target event. To detect a target event, we devise a classifier of tweets based on features such as the keywords in a tweet, the number of words, and their context. Subsequently, we produce a probabilistic spatiotemporal model for the target event that can find the center of the event location. We regard each Twitter user as a sensor and apply particle filtering, which are widely used for location estimation. The particle filter works better than other comparable methods for estimating the locations of target events. As an application, we develop an earthquake reporting system for use in Japan. Because of the numerous earthquakes and the large number of Twitter users throughout the country, we can detect an earthquake with high probability (93 percent of earthquakes of Japan Meteorological Agency (JMA) seismic intensity scale 3 or more are detected) merely by monitoring tweets. Our system detects earthquakes promptly and notification is delivered much faster than JMA broadcast announcements.
  • 25. IEEE- Project Title 2013 25 33,Meenakshi Sundaram Building, Sivaji st, (Near Tnagar Bus Terminus),TNagar Chennai-17, Ph: 044-42070551 Mobile: 9025439777/ www.sybiantechnologies.com / sybianprojects@gmail.com IMAGE PROCESSING 1. Discrete Wavelet Transform and Data Expansion Reduction in Homomorphic Encrypted Domain ABSTRACT: Signal processing in the encrypted domain is a new technology with the goal of protecting valuable signals from insecure signal processing. In this paper, we propose a method for implementing discrete wavelet transform (DWT) and multiresolution analysis (MRA) in homomorphic encrypted domain. We first suggest a framework for performing DWT and inverse DWT (IDWT) in the encrypted domain, then conduct an analysis of data expansion and quantization errors under the framework. To solve the problem of data expansion, which may be very important in practical applications, we present a method for reducing data expansion in the case that both DWT and IDWT are performed. With the proposed method, multilevel DWT/IDWT can be performed with less data expansion in homomorphic encrypted domain. We propose a new signal processing procedure, where the multiplicative inverse method is employed as the last step to limit the data expansion. Taking a 2-D Haar wavelet transform as an example, we conduct a few experiments to demonstrate the advantages of our method in secure image processing. We also provide computational complexity analyses and comparisons. To the best of our knowledge, there has been no report on the implementation of DWT and MRA in the encrypted domain.
  • 26. IEEE- Project Title 2013 26 33,Meenakshi Sundaram Building, Sivaji st, (Near Tnagar Bus Terminus),TNagar Chennai-17, Ph: 044-42070551 Mobile: 9025439777/ www.sybiantechnologies.com / sybianprojects@gmail.com 2. Scanned Document Compression Using Block-Based Hybrid Video Codec ABSTRACT: This paper proposes a hybrid pattern matching/transform-based compression method for scanned documents. The idea is to use regular video interframe prediction as a pattern matching algorithm that can be applied to document coding. We show that this interpretation may generate residual data that can be efficiently compressed by a transform-based encoder. The efficiency of this approach is demonstrated using H.264/advanced video coding (AVC) as a high-quality single and multipage document compressor. The proposed method, called advanced document coding (ADC), uses segments of the originally independent scanned pages of a document to create a video sequence, which is then encoded through regular H.264/AVC. The encoding performance is unrivaled. Results show that ADC outperforms AVC-I (H.264/AVC operating in pure intramode) and JPEG2000 by up to 2.7 and 6.2 dB, respectively. Superior subjective quality is also achieved. 3. Perceptual Quality-Regulable Video Coding System With Region-Based Rate Control Scheme ABSTRACT: In this paper, we discuss a region-based perceptual quality-regulable H.264 video encoder system that we developed. The ability to adjust the quality of specific regions of a source video to a predefined level of quality is an essential
  • 27. IEEE- Project Title 2013 27 33,Meenakshi Sundaram Building, Sivaji st, (Near Tnagar Bus Terminus),TNagar Chennai-17, Ph: 044-42070551 Mobile: 9025439777/ www.sybiantechnologies.com / sybianprojects@gmail.com technique for region-based video applications. We use the structural similarity index as the quality metric for distortion-quantization modeling and develop a bit allocation and rate control scheme for enhancing regional perceptual quality. Exploiting the relationship between the reconstructed macroblock and the best predicted macroblock from mode decision, a novel quantization parameter prediction method is built and used to achieve the target video quality of the processed macroblock. Experimental results show that the system model has only 0.013 quality error in average. Moreover, the proposed region-based rate control system can encode video well under a bitrate constraint with a 0.1% bitrate error in average. For the situation of the low bitrate constraint, the proposed system can encode video with a 0.5% bit error rate in average and enhance the quality of the target regions. 4. General Framework to Histogram-Shifting-Based Reversible Data Hiding ABSTRACT: Histogram shifting (HS) is a useful technique of reversible data hiding (RDH). With HS-based RDH, high capacity and low distortion can be achieved efficiently. In this paper, we revisit the HS technique and present a general framework to construct HS-based RDH. By the proposed framework, one can get a RDH algorithm by simply designing the so-called shifting and embedding functions. Moreover, by taking specific shifting and embedding functions, we show that several RDH algorithms reported in the literature are special cases of this general construction. In addition, two novel and efficient RDH algorithms are also
  • 28. IEEE- Project Title 2013 28 33,Meenakshi Sundaram Building, Sivaji st, (Near Tnagar Bus Terminus),TNagar Chennai-17, Ph: 044-42070551 Mobile: 9025439777/ www.sybiantechnologies.com / sybianprojects@gmail.com introduced to further demonstrate the universality and applicability of our framework. It is expected that more efficient RDH algorithms can be devised according to the proposed framework by carefully designing the shifting and embedding functions. 5. Exploring Visual and Motion Saliency for Automatic Video Object Extraction ABSTRACT: This paper presents a saliency-based video object extraction (VOE) framework. The proposed framework aims to automatically extract foreground objects of interest without any user interaction or the use of any training data (i.e., not limited to any particular type of object). To separate foreground and background regions within and across video frames, the proposed method utilizes visual and motion saliency information extracted from the input video. A conditional random field is applied to effectively combine the saliency induced features, which allows us to deal with unknown pose and scale variations of the foreground object (and its articulated parts). Based on the ability to preserve both spatial continuity and temporal consistency in the proposed VOE framework, experiments on a variety of videos verify that our method is able to produce quantitatively and qualitatively satisfactory VOE results.
  • 29. IEEE- Project Title 2013 29 33,Meenakshi Sundaram Building, Sivaji st, (Near Tnagar Bus Terminus),TNagar Chennai-17, Ph: 044-42070551 Mobile: 9025439777/ www.sybiantechnologies.com / sybianprojects@gmail.com MOBILE COMPUTING 1. Content Sharing over Smartphone-Based Delay-Tolerant Networks ABSTRACT: With the growing number of smartphone users, peer-to-peer ad hoc content sharing is expected to occur more often. Thus, new content sharing mechanisms should be developed as traditional data delivery schemes are not efficient for content sharing due to the sporadic connectivity between smartphones. To accomplish data delivery in such challenging environments, researchers have proposed the use of store-carry-forward protocols, in which a node stores a message and carries it until a forwarding opportunity arises through an encounter with other nodes. Most previous works in this field have focused on the prediction of whether two nodes would encounter each other, without considering the place and time of the encounter. In this paper, we propose discover-predict-deliver as an efficient content sharing scheme for delay-tolerant smartphone networks. In our proposed scheme, contents are shared using the mobility information of individuals. Specifically, our approach employs a mobility learning algorithm to identify places indoors and outdoors. A hidden Markov model is used to predict an individual's future mobility information. Evaluation based on real traces indicates that with the proposed approach, 87 percent of contents can be correctly discovered and delivered within 2 hours when the content is available only in 30 percent of nodes in the network. We implement a sample application on commercial smartphones, and we validate its efficiency to analyze the practical feasibility of
  • 30. IEEE- Project Title 2013 30 33,Meenakshi Sundaram Building, Sivaji st, (Near Tnagar Bus Terminus),TNagar Chennai-17, Ph: 044-42070551 Mobile: 9025439777/ www.sybiantechnologies.com / sybianprojects@gmail.com the content sharing application. Our system approximately results in a 2 percent CPU overhead and reduces the battery lifetime of a smartphone by 15 percent at most. 2. Distributed Cooperative Caching in Social Wireless Networks ABSTRACT: This paper introduces cooperative caching policies for minimizing electronic content provisioning cost in Social Wireless Networks (SWNET). SWNETs are formed by mobile devices, such as data enabled phones, electronic book readers etc., sharing common interests in electronic content, and physically gathering together in public places. Electronic object caching in such SWNETs are shown to be able to reduce the content provisioning cost which depends heavily on the service and pricing dependences among various stakeholders including content providers (CP), network service providers, and End Consumers (EC). Drawing motivation from Amazon's Kindle electronic book delivery business, this paper develops practical network, service, and pricing models which are then used for creating two object caching strategies for minimizing content provisioning costs in networks with homogenous and heterogeneous object demands. The paper constructs analytical and simulation models for analyzing the proposed caching strategies in the presence of selfish users that deviate from network-wide cost- optimal policies. It also reports results from an Android phone-based prototype SWNET, validating the presented analytical and simulation results.
  • 31. IEEE- Project Title 2013 31 33,Meenakshi Sundaram Building, Sivaji st, (Near Tnagar Bus Terminus),TNagar Chennai-17, Ph: 044-42070551 Mobile: 9025439777/ www.sybiantechnologies.com / sybianprojects@gmail.com 3. Predicting Human Movement Based on Telecom's Handoff in Mobile Networks ABSTRACT: Investigating human movement behavior is important for studying issues such as prediction of vehicle traffic and spread of contagious diseases. Since mobile telecom network can efficiently monitor the movement of mobile users, the telecom's mobility management is an ideal mechanism for studying human movement issues. The problem can be abstracted as follows: What is the probability that a person at location A will move to location B after T hours. The answer cannot be directly obtained because commercial telecom networks do not exactly trace the movement history of every mobile user. In this paper, we show how to use the standard outputs (handover rates, call arrival rates, call holding time, and call traffic) measured in a mobile telecom network to derive the answer for this problem. 4. Spatial Distribution and Channel Quality Adaptive Protocol for Multihop Wireless Broadcast Routing in VANET ABSTRACT: Multihop wireless broadcast is an important component in vehicular networks. Many applications are built on broadcast communications, so efficient routing methods are critical for their success. Here, we develop the Distribution- Adaptive Distance with Channel Quality (DADCQ) protocol to address this need and show that it performs well compared to several existing multihop broadcast
  • 32. IEEE- Project Title 2013 32 33,Meenakshi Sundaram Building, Sivaji st, (Near Tnagar Bus Terminus),TNagar Chennai-17, Ph: 044-42070551 Mobile: 9025439777/ www.sybiantechnologies.com / sybianprojects@gmail.com proposals. The DADCQ protocol utilizes the distance method to select forwarding nodes. The performance of this method depends heavily on the value of the decision threshold, but it is difficult to choose a value that results in good performance across all scenarios. Node density, spatial distribution pattern, and wireless channel quality all affect the optimal value. Broadcast protocols tailored to vehicular networking must be adaptive to variation in these factors. In this work, we address this design challenge by creating a decision threshold function that is simultaneously adaptive to the number of neighbors, the node clustering factor, and the Rician fading parameter. To calculate the clustering factor, we propose using the quadrat method of spatial analysis. The resulting DADCQ protocol is then verified with JiST/SWANS and shown to achieve high reachability and low bandwidth consumption in urban and highway scenarios with varying node density and fading intensity. 5. A Robust Indoor Pedestrian Tracking System with Sparse Infrastructure Support ABSTRACT: Existing approaches to indoor tracking have various limitations. Location- fingerprinting approaches are labor intensive and vulnerable to environmental changes. Trilateration approaches require at least three line-of-sight beacons for coverage at any point in the service area, which results in heavy infrastructure cost. Dead reckoning (DR) approaches rely on knowledge of the initial location and suffer from tracking error accumulation. Despite this, we adopt DR for location tracking because of the recent emergence of affordable hand-held devices equipped
  • 33. IEEE- Project Title 2013 33 33,Meenakshi Sundaram Building, Sivaji st, (Near Tnagar Bus Terminus),TNagar Chennai-17, Ph: 044-42070551 Mobile: 9025439777/ www.sybiantechnologies.com / sybianprojects@gmail.com with low-cost DR-enabling sensors. In this paper, we propose an indoor pedestrian tracking system that comprises of a DR subsystem implemented on a mobile phone and a ranging subsystem with a sparse infrastructure. A particle-filter-based fusion scheme is applied to bound the accumulated tracking error by fusing DR with sparse range measurements. Experimental results show that the proposed system is able to track users much better than DR alone. The system is robust even when: 1) the initial user location is not available; 2) range updates are noisy; and 3) range updates are intermittent, both temporally and spatially. 6. A MAC Sensing Protocol Design for Data Transmission with More Protection to Primary Users ABSTRACT: MAC protocols to sense channels for data transmission have been widely investigated for the secondary users to efficiently utilize and share the spectrum licensed by the primary user. One important issue associated with MAC protocols design is how the secondary users determine when and which channel they should sense and access without causing harmful interference to the primary user. In this paper, we jointly consider the MAC-layer spectrum sensing and channel access. Normal Spectrum Sensing (NSS) is required to be carried out at the beginning of each frame to determine whether the channel is idle. On detecting the available transmission opportunity, the secondary users employ CSMA for channel contention. The novelty is that, Fast Spectrum Sensing (FSS) is inserted after channel contention to promptly detect the return of the primary users. This is unlike most other MAC protocols which do not incorporate FSS. Having FSS, the
  • 34. IEEE- Project Title 2013 34 33,Meenakshi Sundaram Building, Sivaji st, (Near Tnagar Bus Terminus),TNagar Chennai-17, Ph: 044-42070551 Mobile: 9025439777/ www.sybiantechnologies.com / sybianprojects@gmail.com primary user can benefit from more protection. A concrete protocol design is provided in this paper, and the throughput-collision tradeoff and utility-collision tradeoff problems are formulated to evaluate its performance. Simulation results demonstrate the efficiency of the proposed MAC protocol with FSS. 7. Cross-Layer Minimum-Delay Scheduling and Maximum-Throughput Resource Allocation for Multiuser Cognitive Networks ABSTRACT: A cognitive network is considered that consists of a base station (BS) communicating with multiple primary and secondary users. Each secondary user can access only one of the orthogonal primary channels. A model is considered in which the primary users can tolerate a certain average delay. A special case is also considered in which the primary users do not suffer from any delay. A novel cross- layer scheme is proposed in which the BS performs successive interference cancellation and thus a secondary user can coexist with an active primary user without adversely affecting its transmission. A scheduling algorithm is proposed that minimizes the average packet delay of the secondary user under constraints on the average power transmitted by the secondary user and the average packet delay of the primary user. A resource allocation algorithm is also proposed to assign the secondary users' channels such that the total throughput of the network is maximized. Our results indicate that the network throughput increases significantly by increasing the number of transmitted packets of the secondary users and/or by allowing a small delay for the primary user packets.
  • 35. IEEE- Project Title 2013 35 33,Meenakshi Sundaram Building, Sivaji st, (Near Tnagar Bus Terminus),TNagar Chennai-17, Ph: 044-42070551 Mobile: 9025439777/ www.sybiantechnologies.com / sybianprojects@gmail.com 8. ALERT: An Anonymous Location-Based Efficient Routing Protocol in MANETs ABSTRACT: Mobile Ad Hoc Networks (MANETs) use anonymous routing protocols that hide node identities and/or routes from outside observers in order to provide anonymity protection. However, existing anonymous routing protocols relying on either hop- by-hop encryption or redundant traffic, either generate high cost or cannot provide full anonymity protection to data sources, destinations, and routes. The high cost exacerbates the inherent resource constraint problem in MANETs especially in multimedia wireless applications. To offer high anonymity protection at a low cost, we propose an Anonymous Location-based Efficient Routing proTocol (ALERT). ALERT dynamically partitions the network field into zones and randomly chooses nodes in zones as intermediate relay nodes, which form a nontraceable anonymous route. In addition, it hides the data initiator/receiver among many initiators/receivers to strengthen source and destination anonymity protection. Thus, ALERT offers anonymity protection to sources, destinations, and routes. It also has strategies to effectively counter intersection and timing attacks. We theoretically analyze ALERT in terms of anonymity and efficiency. Experimental results exhibit consistency with the theoretical analysis, and show that ALERT achieves better route anonymity protection and lower cost compared to other anonymous routing protocols. Also, ALERT achieves comparable routing efficiency to the GPSR geographical routing protocol.
  • 36. IEEE- Project Title 2013 36 33,Meenakshi Sundaram Building, Sivaji st, (Near Tnagar Bus Terminus),TNagar Chennai-17, Ph: 044-42070551 Mobile: 9025439777/ www.sybiantechnologies.com / sybianprojects@gmail.com MULTIMEDIA 1. An Adaptive Cloud Downloading Service ABSTRACT: Video content downloading using the P2P approach is scalable, but does not always give good performance. Recently, subscription-based premium services have emerged, referred to as cloud downloading. In this service, the cloud storage and server caches user-interested content and updates the cache based on user downloading requests. If a requested video is not in the cache, the request is held in a waiting state until the cache is updated. We call this design server mode. An alternative design is to let the cloud server serve all downloading requests as soon as they arrive, behaving as a helper peer. We call this design helper mode. Our model and analysis show that both these designs are useful for certain operating regimes. The helper mode is good at handling a high request rate, while the server mode is good at scaling with video population size. We design an adaptive algorithm (AMS) to select the service mode automatically. Intuitively, AMS switches service mode from server mode to helper mode when too many peers request blocked movies, and vice versa. The ability of AMS to achieve good performance in different operating regimes is validated by simulation .
  • 37. IEEE- Project Title 2013 37 33,Meenakshi Sundaram Building, Sivaji st, (Near Tnagar Bus Terminus),TNagar Chennai-17, Ph: 044-42070551 Mobile: 9025439777/ www.sybiantechnologies.com / sybianprojects@gmail.com 2. Efficient Resource Provisioning and Rate Selection for Stream Mining in a Community Cloud ABSTRACT: Real-time stream mining such as surveillance and personal health monitoring, which involves sophisticated mathematical operations, is computation- intensive and prohibitive for mobile devices due to the hardware/computation constraints. To satisfy the growing demand for stream mining in mobile networks, we propose to employ a cloud-based stream mining system in which the mobile devices send via wireless links unclassified media streams to the cloud for classification. We aim at minimizing the classification-energy cost, defined as an affine combination of classification cost and energy consumption at the cloud, subject to an average stream mining delay constraint (which is important in real- time applications). To address the challenge of time-varying wireless channel conditions without a priori information about the channel statistics, we develop an online algorithm in which the cloud operator can dynamically adjust its resource provisioning on the fly and the mobile devices can adapt their transmission rates to the instantaneous channel conditions. It is proved that, at the expense of increasing the average stream mining delay, the online algorithm achieves a classification- energy cost that can be pushed arbitrarily close to the minimum cost achieved by the optimal offline algorithm. Extensive simulations are conducted to validate the analysis.
  • 38. IEEE- Project Title 2013 38 33,Meenakshi Sundaram Building, Sivaji st, (Near Tnagar Bus Terminus),TNagar Chennai-17, Ph: 044-42070551 Mobile: 9025439777/ www.sybiantechnologies.com / sybianprojects@gmail.com 3. Cloud-Based Image Coding for Mobile Devices—Toward Thousands to One Compression ABSTRACT: Current image coding schemes make it hard to utilize external images for compression even if highly correlated images can be found in the cloud. To solve this problem, we propose a method of cloud-based image coding that is different from current image coding even on the ground. It no longer compresses images pixel by pixel and instead tries to describe images and reconstruct them from a large-scale image database via the descriptions. First, we describe an input image based on its down-sampled version and local feature descriptors. The descriptors are used to retrieve highly correlated images in the cloud and identify corresponding patches. The down-sampled image serves as a target to stitch retrieved image patches together. Second, the down-sampled image is compressed using current image coding. The feature vectors of local descriptors are predicted by the corresponding vectors extracted in the decoded down-sampled image. The predicted residual vectors are compressed by transform, quantization, and entropy coding. The experimental results show that the visual quality of reconstructed images is significantly better than that of intra-frame coding in HEVC and JPEG at thousands to one compression .
  • 39. IEEE- Project Title 2013 39 33,Meenakshi Sundaram Building, Sivaji st, (Near Tnagar Bus Terminus),TNagar Chennai-17, Ph: 044-42070551 Mobile: 9025439777/ www.sybiantechnologies.com / sybianprojects@gmail.com 4. Optimizing Cloud Resources for Delivering IPTV Services Through Virtualization ABSTRACT: Virtualized cloud-based services can take advantage of statistical multiplexing across applications to yield significant cost savings. However, achieving similar savings with real-time services can be a challenge. In this paper, we seek to lower a provider's costs for real-time IPTV services through a virtualized IPTV architecture and through intelligent time-shifting of selected services. Using Live TV and Video-on-Demand (VoD) as examples, we show that we can take advantage of the different deadlines associated with each service to effectively multiplex these services. We provide a generalized framework for computing the amount of resources needed to support multiple services, without missing the deadline for any service. We construct the problem as an optimization formulation that uses a generic cost function. We consider multiple forms for the cost function (e.g., maximum, convex and concave functions) reflecting the cost of providing the service. The solution to this formulation gives the number of servers needed at different time instants to support these services. We implement a simple mechanism for time-shifting scheduled jobs in a simulator and study the reduction in server load using real traces from an operational IPTV network. Our results show that we are able to reduce the load by ~24%(compared to a possible ~31.3% as predicted by the optimization framework).
  • 40. IEEE- Project Title 2013 40 33,Meenakshi Sundaram Building, Sivaji st, (Near Tnagar Bus Terminus),TNagar Chennai-17, Ph: 044-42070551 Mobile: 9025439777/ www.sybiantechnologies.com / sybianprojects@gmail.com 5. A Network and Device Aware QoS Approach for Cloud-Based Mobile Streaming ABSTRACT: Cloud multimedia services provide an efficient, flexible, and scalable data processing method and offer a solution for the user demands of high quality and diversified multimedia. As intelligent mobile phones and wireless networks become more and more popular, network services for users are no longer limited to the home. Multimedia information can be obtained easily using mobile devices, allowing users to enjoy ubiquitous network services. Considering the limited bandwidth available for mobile streaming and different device requirements, this study presented a network and device-aware Quality of Service (QoS) approach that provides multimedia data suitable for a terminal unit environment via interactive mobile streaming services, further considering the overall network environment and adjusting the interactive transmission frequency and the dynamic multimedia transcoding, to avoid the waste of bandwidth and terminal power. Finally, this study realized a prototype of this architecture to validate the feasibility of the proposed method. According to the experiment, this method could provide efficient self-adaptive multimedia streaming services for varying bandwidth environments.
  • 41. IEEE- Project Title 2013 41 33,Meenakshi Sundaram Building, Sivaji st, (Near Tnagar Bus Terminus),TNagar Chennai-17, Ph: 044-42070551 Mobile: 9025439777/ www.sybiantechnologies.com / sybianprojects@gmail.com NETWORK SECURITY 1. To Lie or to Comply: Defending against Flood Attacks in Disruption Tolerant Networks ABSTRACT: Disruption Tolerant Networks (DTNs) utilize the mobility of nodes and the opportunistic contacts among nodes for data communications. Due to the limitation in network resources such as contact opportunity and buffer space, DTNs are vulnerable to flood attacks in which attackers send as many packets or packet replicas as possible to the network, in order to deplete or overuse the limited network resources. In this paper, we employ rate limiting to defend against flood attacks in DTNs, such that each node has a limit over the number of packets that it can generate in each time interval and a limit over the number of replicas that it can generate for each packet. We propose a distributed scheme to detect if a node has violated its rate limits. To address the challenge that it is difficult to count all the packets or replicas sent by a node due to lack of communication infrastructure, our detection adopts claim-carry-and-check: each node itself counts the number of packets or replicas that it has sent and claims the count to other nodes; the receiving nodes carry the claims when they move, and cross-check if their carried claims are inconsistent when they contact. The claim structure uses the pigeonhole principle to guarantee that an attacker will make inconsistent claims which may lead to detection. We provide rigorous analysis on the probability of detection, and
  • 42. IEEE- Project Title 2013 42 33,Meenakshi Sundaram Building, Sivaji st, (Near Tnagar Bus Terminus),TNagar Chennai-17, Ph: 044-42070551 Mobile: 9025439777/ www.sybiantechnologies.com / sybianprojects@gmail.com evaluate the effectiveness and efficiency of our scheme with extensive trace-driven simulations. 2. Design and Implementation of TARF: A Trust-Aware Routing Framework for WSNs ABSTRACT: The multihop routing in wireless sensor networks (WSNs) offers little protection against identity deception through replaying routing information. An adversary can exploit this defect to launch various harmful or even devastating attacks against the routing protocols, including sinkhole attacks, wormhole attacks, and Sybil attacks. The situation is further aggravated by mobile and harsh network conditions. Traditional cryptographic techniques or efforts at developing trust- aware routing protocols do not effectively address this severe problem. To secure the WSNs against adversaries misdirecting the multihop routing, we have designed and implemented TARF, a robust trust-aware routing framework for dynamic WSNs. Without tight time synchronization or known geographic information, TARF provides trustworthy and energy-efficient route. Most importantly, TARF proves effective against those harmful attacks developed out of identity deception; the resilience of TARF is verified through extensive evaluation with both simulation and empirical experiments on large-scale WSNs under various scenarios including mobile and RF-shielding network conditions. Further, we have implemented a low-overhead TARF module in TinyOS; as demonstrated, this implementation can be incorporated into existing routing protocols with the least
  • 43. IEEE- Project Title 2013 43 33,Meenakshi Sundaram Building, Sivaji st, (Near Tnagar Bus Terminus),TNagar Chennai-17, Ph: 044-42070551 Mobile: 9025439777/ www.sybiantechnologies.com / sybianprojects@gmail.com effort. Based on TARF, we also demonstrated a proof-of-concept mobile target detection application that functions well against an antidetection mechanism. 3. Towards Trustworthy Resource Scheduling in Clouds ABSTRACTS: Managing the allocation of cloud virtual machines at physical resources is a key requirement for the success of clouds. Current implementations of cloud schedulers do not consider the entire cloud infrastructure neither do they consider the overall user and infrastructure properties. This results in major security, privacy, and resilience concerns. In this paper, we propose a novel cloud scheduler which considers both user requirements and infrastructure properties. We focus on assuring users that their virtual resources are hosted using physical resources that match their requirements without getting users involved with understanding the details of the cloud infrastructure. As a proof-of-concept, we present our prototype which is built on OpenStack. The provided prototype implements the proposed cloud scheduler. It also provides an implementation of our previous work on cloud trust management which provides the scheduler with input about the trust status of the cloud infrastructure. 4. A Hierarchical Approach for the Resource Management of Very Large Cloud Platforms ABSTRACT: Worldwide interest in the delivery of computing and storage capacity as a service continues to grow at a rapid pace. The complexities of such cloud
  • 44. IEEE- Project Title 2013 44 33,Meenakshi Sundaram Building, Sivaji st, (Near Tnagar Bus Terminus),TNagar Chennai-17, Ph: 044-42070551 Mobile: 9025439777/ www.sybiantechnologies.com / sybianprojects@gmail.com computing centers require advanced resource management solutions that are capable of dynamically adapting the cloud platform while providing continuous service and performance guarantees. The goal of this paper is to devise resource allocation policies for virtualized cloud environments that satisfy performance and availability guarantees and minimize energy costs in very large cloud service centers. We present a scalable distributed hierarchical framework based on a mixed-integer non-linear optimization for resource management acting at multiple time-scales. Extensive experiments across a wide variety of configurations demonstrate the efficiency and effectiveness of our approach. 5. CAM: Cloud-Assisted Privacy Preserving Mobile Health Monitoring ABSTRACT: Cloud-assisted mobile health (mHealth) monitoring, which applies the prevailing mobile communications and cloud computing technologies to provide feedback decision support, has been considered as a revolutionary approach to improving the quality of healthcare service while lowering the healthcare cost. Unfortunately, it also poses a serious risk on both clients' privacy and intellectual property of monitoring service providers, which could deter the wide adoption of mHealth technology. This paper is to address this important problem and design a cloud-assisted privacy preserving mobile health monitoring system to protect the privacy of the involved parties and their data. Moreover, the outsourcing decryption technique and a newly proposed key private proxy reencryption are adapted to shift the computational complexity of the involved parties to the cloud without compromising clients' privacy and service providers' intellectual property. Finally, our security and performance analysis demonstrates the effectiveness of our proposed design.
  • 45. IEEE- Project Title 2013 45 33,Meenakshi Sundaram Building, Sivaji st, (Near Tnagar Bus Terminus),TNagar Chennai-17, Ph: 044-42070551 Mobile: 9025439777/ www.sybiantechnologies.com / sybianprojects@gmail.com NETWORKING 1. An Effective Network Traffic Classification Method with Unknown Flow Detection ABSTRACT: Traffic classification technique is an essential tool for network and system security in the complex environments such as cloud computing based environment. The state-of-the-art traffic classification methods aim to take the advantages of flow statistical features and machine learning techniques, however the classification performance is severely affected by limited supervised information and unknown applications. To achieve effective network traffic classification, we propose a new method to tackle the problem of unknown applications in the crucial situation of a small supervised training set. The proposed method possesses the superior capability of detecting unknown flows generated by unknown applications and utilizing the correlation information among real-world network traffic to boost the classification performance. A theoretical analysis is provided to confirm performance benefit of the proposed method. Moreover, the comprehensive performance evaluation conducted on two real-world network traffic datasets shows that the proposed scheme outperforms the existing methods in the critical network environment.
  • 46. IEEE- Project Title 2013 46 33,Meenakshi Sundaram Building, Sivaji st, (Near Tnagar Bus Terminus),TNagar Chennai-17, Ph: 044-42070551 Mobile: 9025439777/ www.sybiantechnologies.com / sybianprojects@gmail.com 2. Hierarchical Trust Management for Wireless Sensor Networks and its Applications to Trust-Based Routing and Intrusion Detection ABSTRACT: We propose a highly scalable cluster-based hierarchical trust management protocol for wireless sensor networks (WSNs) to effectively deal with selfish or malicious nodes. Unlike prior work, we consider multidimensional trust attributes derived from communication and social networks to evaluate the overall trust of a sensor node. By means of a novel probability model, we describe a heterogeneous WSN comprising a large number of sensor nodes with vastly different social and quality of service (QoS) behaviors with the objective to yield "ground truth" node status. This serves as a basis for validating our protocol design by comparing subjective trust generated as a result of protocol execution at runtime against objective trust obtained from actual node status. To demonstrate the utility of our hierarchical trust management protocol, we apply it to trust-based geographic routing and trust-based intrusion detection. For each application, we identify the best trust composition and formation to maximize application performance. Our results indicate that trust-based geographic routing approaches the ideal performance level achievable by flooding-based routing in message delivery ratio and message delay without incurring substantial message overhead. For trust-based intrusion detection, we discover that there exists an optimal trust threshold for minimizing false positives and false negatives. Furthermore, trust-based intrusion detection outperforms traditional anomaly-based intrusion detection approaches in both the detection probability and the false positive probability.
  • 47. IEEE- Project Title 2013 47 33,Meenakshi Sundaram Building, Sivaji st, (Near Tnagar Bus Terminus),TNagar Chennai-17, Ph: 044-42070551 Mobile: 9025439777/ www.sybiantechnologies.com / sybianprojects@gmail.com 3. Torrents on Twitter: Explore Long-Term Social Relationships in Peer- to-Peer Systems ABSTRACT: Peer-to-peer file sharing systems, most notably BitTorrent (BT), have achieved tremendous success among Internet users. Recent studies suggest that the long-term relationships among BT peers can be explored to enhance the downloading performance; for example, for re-sharing previously downloaded contents or for effectively collaborating among the peers. However, whether such relationships do exist in real world remains unclear. In this paper, we take a first step towards the real-world applicability of peers' long-term relationship through a measurement based study. We find that 95% peers cannot even meet each other again in the BT networks; therefore, most peers can hardly be organized for further cooperation. This result contradicts to the conventional understanding based on the observed daily arrival pattern in peer-to-peer networks. To better understand this, we revisit the arrival of BT peers as well as their long-range dependence. We find that the peers' arrival patterns are highly diverse; only a limited number of stable peers have clear self-similar and periodic daily arrivals patterns. The arrivals of most peers are, however, quite random with little evidence of long-range dependence. To better utilize these stable peers, we start to explore peers' long- term relationships in specific swarms instead of conventional BT networks. Fortunately, we find that the peers in Twitter-initialized torrents have stronger temporal locality, thus offering great opportunity for improving their degree of sharing. Our PlanetLab experiments further indicate that the incorporation of social
  • 48. IEEE- Project Title 2013 48 33,Meenakshi Sundaram Building, Sivaji st, (Near Tnagar Bus Terminus),TNagar Chennai-17, Ph: 044-42070551 Mobile: 9025439777/ www.sybiantechnologies.com / sybianprojects@gmail.com relations remarkably accelerates the download completion time. The improvement remains noticeable even in a hybrid system with a small set of social friends only. 4. Efficient Storage and Processing of High-Volume Network Monitoring Data ABSTRACT: Monitoring modern networks involves storing and transferring huge amounts of data. To cope with this problem, in this paper we propose a technique that allows to transform the measurement data in a representation format meeting two main objectives at the same time. Firstly, it allows to perform a number of operations directly on the transformed data with a controlled loss of accuracy, thanks to the mathematical framework it is based on. Secondly, the new representation has a small memory footprint, allowing to reduce the space needed for data storage and the time needed for data transfer. To validate our technique, we perform an analysis of its performance in terms of accuracy and memory footprint. The results show that the transformed data closely approximates the original data (within 5% relative error) while achieving a compression ratio of 20%; storage footprint can also be gradually reduced towards the one of the state- of-the-art compression tools, such as bzip2, if higher approximation is allowed. Finally, a sensibility analysis show that technique allows to trade-off the accuracy on different input fields so to accommodate for specific application needs, while a scalability analysis indicates that the technique scales with input size spanning up to three orders of magnitude.
  • 49. IEEE- Project Title 2013 49 33,Meenakshi Sundaram Building, Sivaji st, (Near Tnagar Bus Terminus),TNagar Chennai-17, Ph: 044-42070551 Mobile: 9025439777/ www.sybiantechnologies.com / sybianprojects@gmail.com 5. An Efficient and Robust Addressing Protocol for Node Autoconfiguration in Ad Hoc Networks ABSTRACT: Address assignment is a key challenge in ad hoc networks due to the lack of infrastructure. Autonomous addressing protocols require a distributed and self- managed mechanism to avoid address collisions in a dynamic network with fading channels, frequent partitions, and joining/leaving nodes. We propose and analyze a lightweight protocol that configures mobile ad hoc nodes based on a distributed address database stored in filters that reduces the control load and makes the proposal robust to packet losses and network partitions. We evaluate the performance of our protocol, considering joining nodes, partition merging events, and network initialization. Simulation results show that our protocol resolves all the address collisions and also reduces the control traffic when compared to previously proposed protocols. 6. Complexity Analysis and Algorithm Design for Advance Bandwidth Scheduling in Dedicated Networks ABSTRACT: An increasing number of high-performance networks provision dedicated channels through circuit switching or MPLS/GMPLS techniques to support large data transfer. The link bandwidths in such networks are typically shared by multiple users through advance reservation, resulting in varying bandwidth
  • 50. IEEE- Project Title 2013 50 33,Meenakshi Sundaram Building, Sivaji st, (Near Tnagar Bus Terminus),TNagar Chennai-17, Ph: 044-42070551 Mobile: 9025439777/ www.sybiantechnologies.com / sybianprojects@gmail.com availability in future time. Developing efficient scheduling algorithms for advance bandwidth reservation has become a critical task to improve the utilization of network resources and meet the transport requirements of application users. We consider an exhaustive combination of different path and bandwidth constraints and formulate four types of advance bandwidth scheduling problems, with the same objective to minimize the data transfer end time for a given transfer request with a prespecified data size: fixed path with fixed bandwidth (FPFB); fixed path with variable bandwidth (FPVB); variable path with fixed bandwidth (VPFB); and variable path with variable bandwidth (VPVB). For VPFB and VPVB, we further consider two subcases where the path switching delay is negligible or nonnegligible. We propose an optimal algorithm for each of these scheduling problems except for FPVB and VPVB with nonnegligible path switching delay, which are proven to be NP-complete and nonapproximable, and then tackled by heuristics. The performance superiority of these heuristics is verified by extensive experimental results in a large set of simulated networks in comparison to optimal and greedy strategies. 7. Distortion-Aware Scalable Video Streaming to Multinetwork Clients ABSTRACT: We consider the problem of scalable video streaming from a server to multinetwork clients over heterogeneous access networks, with the goal of minimizing the distortion of the received videos. This problem has numerous applications including: 1) mobile devices connecting to multiple licensed and ISM bands, and 2) cognitive multiradio devices employing spectrum bonding. In this
  • 51. IEEE- Project Title 2013 51 33,Meenakshi Sundaram Building, Sivaji st, (Near Tnagar Bus Terminus),TNagar Chennai-17, Ph: 044-42070551 Mobile: 9025439777/ www.sybiantechnologies.com / sybianprojects@gmail.com paper, we ascertain how to optimally determine which video packets to transmit over each access network. We present models to capture the network conditions and video characteristics and develop an integer program for deterministic packet scheduling. Solving the integer program exactly is typically not computationally tractable, so we develop heuristic algorithms for deterministic packet scheduling, as well as convex optimization problems for randomized packet scheduling. We carry out a thorough study of the tradeoff between performance and computational complexity and propose a convex programming-based algorithm that yields good performance while being suitable for real-time applications. We conduct extensive trace-driven simulations to evaluate the proposed algorithms using real network conditions and scalable video streams. The simulation results show that the proposed convex programming-based algorithm: 1) outperforms the rate control algorithms defined in the Datagram Congestion Control Protocol (DCCP) by about 10-15 dB higher video quality; 2) reduces average delivery delay by over 90% compared to DCCP; 3) results in higher average video quality of 4.47 and 1.92 dB than the two developed heuristics; 4) runs efficiently, up to six times faster than the best-performing heuristic; and 5) does indeed provide service differentiation among users. 8. Exploring the Design Space of Multichannel Peer-to-Peer Live Video Streaming Systems ABSTRACT: Most of the commercial peer-to-peer (P2P) video streaming deployments support hundreds of channels and are referred to as multichannel systems. Recent
  • 52. IEEE- Project Title 2013 52 33,Meenakshi Sundaram Building, Sivaji st, (Near Tnagar Bus Terminus),TNagar Chennai-17, Ph: 044-42070551 Mobile: 9025439777/ www.sybiantechnologies.com / sybianprojects@gmail.com research studies have proposed specific protocols to improve the streaming quality for all channels by enabling cross-channel cooperation among multiple channels. In this paper, we focus on the following fundamental problems in designing cooperating multichannel systems: 1) what are the general characteristics of existing and potential designs? and 2) under what circumstances should a particular design be used to achieve the desired streaming quality with the lowest implementation complexity? To answer the first question, we propose simple models based on linear programming and network-flow graphs for three general designs, namely Naive Bandwidth allocation Approach (NBA), Passive Channel- aware bandwidth allocation Approach (PCA), and Active Channel-aware bandwidth allocation Approach (ACA), which provide insight into understanding the key characteristics of cross-channel resource sharing. For the second question, we first develop closed-form results for two-channel systems. Then, we use extensive numerical simulations to compare the three designs for various peer population distributions, upload bandwidth distributions, and channel structures. Our analytical and simulation results show that: 1) the NBA design can rarely achieve the desired streaming quality in general cases; 2) the PCA design can achieve the same performance as the ACA design in general cases; and 3) the ACA design should be used for special applications.
  • 53. IEEE- Project Title 2013 53 33,Meenakshi Sundaram Building, Sivaji st, (Near Tnagar Bus Terminus),TNagar Chennai-17, Ph: 044-42070551 Mobile: 9025439777/ www.sybiantechnologies.com / sybianprojects@gmail.com PARALLEL AND DISTRIBUTED SYSTEM 1. Efficient Resource Mapping Framework over Networked Clouds via Iterated Local Search-Based Request Partitioning ABSTRACT: The cloud represents a computing paradigm where shared configurable resources are provided as a service over the Internet. Adding intra- or intercloud communication resources to the resource mix leads to a networked cloud computing environment. Following the cloud infrastructure as a Service paradigm and in order to create a flexible management framework, it is of paramount importance to address efficiently the resource mapping problem within this context. To deal with the inherent complexity and scalability issue of the resource mapping problem across different administrative domains, in this paper a hierarchical framework is described. First, a novel request partitioning approach based on Iterated Local Search is introduced that facilitates the cost-efficient and online splitting of user requests among eligible cloud service providers (CPs) within a networked cloud environment. Following and capitalizing on the outcome of the request partitioning phase, the embedding phase-where the actual mapping of requested virtual to physical resources is performed can be realized through the use of a distributed intracloud resource mapping approach that allows for efficient and balanced allocation of cloud resources. Finally, a thorough evaluation of the proposed overall framework on a simulated networked cloud environment is
  • 54. IEEE- Project Title 2013 54 33,Meenakshi Sundaram Building, Sivaji st, (Near Tnagar Bus Terminus),TNagar Chennai-17, Ph: 044-42070551 Mobile: 9025439777/ www.sybiantechnologies.com / sybianprojects@gmail.com provided and critically compared against an exact request partitioning solution as well as another common intradomain virtual resource embedding solution. 2. A Highly Practical Approach toward Achieving Minimum Data Sets Storage Cost in the Cloud ABSTRACT: Massive computation power and storage capacity of cloud computing systems allow scientists to deploy computation and data intensive applications without infrastructure investment, where large application data sets can be stored in the cloud. Based on the pay-as-you-go model, storage strategies and benchmarking approaches have been developed for cost-effectively storing large volume of generated application data sets in the cloud. However, they are either insufficiently cost-effective for the storage or impractical to be used at runtime. In this paper, toward achieving the minimum cost benchmark, we propose a novel highly cost-effective and practical storage strategy that can automatically decide whether a generated data set should be stored or not at runtime in the cloud. The main focus of this strategy is the local-optimization for the tradeoff between computation and storage, while secondarily also taking users' (optional) preferences on storage into consideration. Both theoretical analysis and simulations conducted on general (random) data sets as well as specific real world applications with Amazon's cost model show that the cost-effectiveness of our strategy is close
  • 55. IEEE- Project Title 2013 55 33,Meenakshi Sundaram Building, Sivaji st, (Near Tnagar Bus Terminus),TNagar Chennai-17, Ph: 044-42070551 Mobile: 9025439777/ www.sybiantechnologies.com / sybianprojects@gmail.com to or even the same as the minimum cost benchmark, and the efficiency is very high for practical runtime utilization in the cloud. 3. Optimal Multiserver Configuration for Profit Maximization in Cloud Computing ABSTRACT: As cloud computing becomes more and more popular, understanding the economics of cloud computing becomes critically important. To maximize the profit, a service provider should understand both service charges and business costs, and how they are determined by the characteristics of the applications and the configuration of a multiserver system. The problem of optimal multiserver configuration for profit maximization in a cloud computing environment is studied. Our pricing model takes such factors into considerations as the amount of a service, the workload of an application environment, the configuration of a multiserver system, the service-level agreement, the satisfaction of a consumer, the quality of a service, the penalty of a low-quality service, the cost of renting, the cost of energy consumption, and a service provider's margin and profit. Our approach is to treat a multiserver system as an M/M/m queuing model, such that our optimization problem can be formulated and solved analytically. Two server speed and power consumption models are considered, namely, the idle-speed model and the constant-speed model. The probability density function of the waiting time of a newly arrived service request is derived. The expected service charge to a service request is calculated. The expected net business gain in one unit
  • 56. IEEE- Project Title 2013 56 33,Meenakshi Sundaram Building, Sivaji st, (Near Tnagar Bus Terminus),TNagar Chennai-17, Ph: 044-42070551 Mobile: 9025439777/ www.sybiantechnologies.com / sybianprojects@gmail.com of time is obtained. Numerical calculations of the optimal server size and the optimal server speed are demonstrated. 4. Anchor: A Versatile and Efficient Framework for Resource Management in the Cloud ABSTRACT: We present Anchor, a general resource management architecture that uses the stable matching framework to decouple policies from mechanisms when mapping virtual machines to physical servers. In Anchor, clients and operators are able to express a variety of distinct resource management policies as they deem fit, and these policies are captured as preferences in the stable matching framework. The highlight of Anchor is a new many-to-one stable matching theory that efficiently matches VMs with heterogeneous resource needs to servers, using both offline and online algorithms. Our theoretical analyses show the convergence and optimality of the algorithm. Our experiments with a prototype implementation on a 20-node server cluster, as well as large-scale simulations based on real-world workload traces, demonstrate that the architecture is able to realize a diverse set of policy objectives with good performance and practicality. 5. Load Rebalancing for Distributed File Systems in Clouds ABSTRACT: Distributed file systems are key building blocks for cloud computing applications based on the MapReduce programming paradigm. In such file systems, nodes simultaneously serve computing and storage functions; a file is
  • 57. IEEE- Project Title 2013 57 33,Meenakshi Sundaram Building, Sivaji st, (Near Tnagar Bus Terminus),TNagar Chennai-17, Ph: 044-42070551 Mobile: 9025439777/ www.sybiantechnologies.com / sybianprojects@gmail.com partitioned into a number of chunks allocated in distinct nodes so that MapReduce tasks can be performed in parallel over the nodes. However, in a cloud computing environment, failure is the norm, and nodes may be upgraded, replaced, and added in the system. Files can also be dynamically created, deleted, and appended. This results in load imbalance in a distributed file system; that is, the file chunks are not distributed as uniformly as possible among the nodes. Emerging distributed file systems in production systems strongly depend on a central node for chunk reallocation. This dependence is clearly inadequate in a large-scale, failure-prone environment because the central load balancer is put under considerable workload that is linearly scaled with the system size, and may thus become the performance bottleneck and the single point of failure. In this paper, a fully distributed load rebalancing algorithm is presented to cope with the load imbalance problem. Our algorithm is compared against a centralized approach in a production system and a competing distributed solution presented in the literature. The simulation results indicate that our proposal is comparable with the existing centralized approach and considerably outperforms the prior distributed algorithm in terms of load imbalance factor, movement cost, and algorithmic overhead. The performance of our proposal implemented in the Hadoop distributed file system is further investigated in a cluster environment.
  • 58. IEEE- Project Title 2013 58 33,Meenakshi Sundaram Building, Sivaji st, (Near Tnagar Bus Terminus),TNagar Chennai-17, Ph: 044-42070551 Mobile: 9025439777/ www.sybiantechnologies.com / sybianprojects@gmail.com SERVICE COMPUTING 1. Optimization of Resource Provisioning Cost in Cloud Computing ABSTRACT: In cloud computing, cloud providers can offer cloud consumers two provisioning plans for computing resources, namely reservation and on-demand plans. In general, cost of utilizing computing resources provisioned by reservation plan is cheaper than that provisioned by on-demand plan, since cloud consumer has to pay to provider in advance. With the reservation plan, the consumer can reduce the total resource provisioning cost. However, the best advance reservation of resources is difficult to be achieved due to uncertainty of consumer's future demand and providers' resource prices. To address this problem, an optimal cloud resource provisioning (OCRP) algorithm is proposed by formulating a stochastic programming model. The OCRP algorithm can provision computing resources for being used in multiple provisioning stages as well as a long-term plan, e.g., four stages in a quarter plan and twelve stages in a yearly plan. The demand and price uncertainty is considered in OCRP. In this paper, different approaches to obtain the solution of the OCRP algorithm are considered including deterministic equivalent formulation, sample-average approximation, and Benders decomposition. Numerical studies are extensively performed in which the results clearly show that with the OCRP algorithm, cloud consumer can successfully minimize total cost of resource provisioning in cloud computing environments.
  • 59. IEEE- Project Title 2013 59 33,Meenakshi Sundaram Building, Sivaji st, (Near Tnagar Bus Terminus),TNagar Chennai-17, Ph: 044-42070551 Mobile: 9025439777/ www.sybiantechnologies.com / sybianprojects@gmail.com 2. Interacting with the SOA-Based Internet of Things: Discovery, Query, Selection, and On-Demand Provisioning of Web Services ABSTRACT: The increasing usage of smart embedded devices in business blurs the line between the virtual and real worlds. This creates new opportunities to build applications that better integrate real-time state of the physical world, and hence, provides enterprise services that are highly dynamic, more diverse, and efficient. Service-Oriented Architecture (SOA) approaches traditionally used to couple functionality of heavyweight corporate IT systems, are becoming applicable to embedded real-world devices, i.e., objects of the physical world that feature embedded processing and communication. In such infrastructures, composed of large numbers of networked, resource-limited devices, the discovery of services and on-demand provisioning of missing functionality is a significant challenge. We propose a process and a suitable system architecture that enables developers and business process designers to dynamically query, select, and use running instances of real-world services (i.e., services running on physical devices) or even deploy new ones on-demand, all in the context of composite, real-world business applications.
  • 60. IEEE- Project Title 2013 60 33,Meenakshi Sundaram Building, Sivaji st, (Near Tnagar Bus Terminus),TNagar Chennai-17, Ph: 044-42070551 Mobile: 9025439777/ www.sybiantechnologies.com / sybianprojects@gmail.com 3. Message-Efficient Service Management Schemes for MOM-Based UPnP Networks ABSTRACT: The use of message-oriented middleware (MOM) in pervasive systems has increased noticeably because of its flexible and failure-tolerant nature. Meanwhile, decentralized service management protocols such as UPnP are believed to be more suitable for administrating applications in small-scale pervasive environments such as smart homes. However, administering MOM-based pervasive systems by UPnP often suffers from network flood problems due to the replications of too many unnecessary messages. This paper presents several traffic reduction schemes, namely, decomposing the multicast traffic, service-based node searching, heartbeat by decomposing the multicast traffic, and on-demand heartbeat, which reduce the replications of unnecessary messages in MOM-based UPnP networks. The analytical predictions agree well with the simulated and experimental results, which show that the message counts of presence and leave announcements, node searching, and heartbeat can be greatly reduced. 4. Toward Trustworthy Coordination of Web Services Business Activities ABSTRACT: We present a lightweight Byzantine fault tolerance (BFT) algorithm, which can be used to render the coordination of web services business activities (WS-BA) more trustworthy. The lightweight design of the BFT algorithm is the result of a comprehensive study of the threats to the WS-BA coordination services and a
  • 61. IEEE- Project Title 2013 61 33,Meenakshi Sundaram Building, Sivaji st, (Near Tnagar Bus Terminus),TNagar Chennai-17, Ph: 044-42070551 Mobile: 9025439777/ www.sybiantechnologies.com / sybianprojects@gmail.com careful analysis of the state model of WS-BA. The lightweight BFT algorithm uses source ordering, rather than total ordering, of incoming requests to achieve Byzantine fault tolerant, state-machine replication of the WS-BA coordination services. We have implemented the lightweight BFT algorithm, and incorporated it into the open-source Kandula framework, which implements the WS-BA specification with the WS-BA-I extension. Performance evaluation results obtained from the prototype implementation confirm the efficiency and effectiveness of our lightweight BFT algorithm, compared to traditional BFT techniques. 5. Dynamic Service Contract Enforcement in Service-Oriented Networks ABSTRACT: In recent years, service-oriented architectures (SOA) have emerged as the main solution for the integration of legacy systems with new technologies in the enterprise world. A service is usually governed by a client service contract (CSC) that specifies, among other requirements, the rate at which a service should be accessed, and limits it to no more than a number of service requests during an observation period. Several approaches, using both static and dynamic credit-based strategies, have been developed to enforce the rate specified in the CSC. Existing approaches have problems related to starvation, approximations used in calculations, and rapid credit consumption under certain conditions. In this paper, we propose and validate DoWSS, a doubly weighted algorithm for service traffic shaping. We show via simulation that DoWSS possesses several advantages: It eliminates the approximation issues, prevents starvation, and contains the rapid credit consumption issue in existing credit-based approaches.
  • 62. IEEE- Project Title 2013 62 33,Meenakshi Sundaram Building, Sivaji st, (Near Tnagar Bus Terminus),TNagar Chennai-17, Ph: 044-42070551 Mobile: 9025439777/ www.sybiantechnologies.com / sybianprojects@gmail.com 6. A Two-Tiered On-Demand Resource Allocation Mechanism for VM- Based Data Centers ABSTRACT: In a shared virtual computing environment, dynamic load changes as well as different quality requirements of applications in their lifetime give rise to dynamic and various capacity demands, which results in lower resource utilization and application quality using the existing static resource allocation. Furthermore, the total required capacities of all the hosted applications in current enterprise data centers, for example, Google, may surpass the capacities of the platform. In this paper, we argue that the existing techniques by turning on or off servers with the help of virtual machine (VM) migration is not enough. Instead, finding an optimized dynamic resource allocation method to solve the problem of on-demand resource provision for VMs is the key to improve the efficiency of data centers. However, the existing dynamic resource allocation methods only focus on either the local optimization within a server or central global optimization, limiting the efficiency of data centers. We propose a two-tiered on-demand resource allocation mechanism consisting of the local and global resource allocation with feedback to provide on-demand capacities to the concurrent applications. We model the on- demand resource allocation using optimization theory. Based on the proposed dynamic resource allocation mechanism and model, we propose a set of on- demand resource allocation algorithms. Our algorithms preferentially ensure performance of critical applications named by the data center manager when resource competition arises according to the time-varying capacity demands and
  • 63. IEEE- Project Title 2013 63 33,Meenakshi Sundaram Building, Sivaji st, (Near Tnagar Bus Terminus),TNagar Chennai-17, Ph: 044-42070551 Mobile: 9025439777/ www.sybiantechnologies.com / sybianprojects@gmail.com the quality of applications. Using Rainbow, a Xen-based prototype we implemented, we evaluate the VM-based shared platform as well as the two-tiered on-demand resource allocation mechanism and algorithms. The experimental results show that Rainbow without dynamic resource allocation (Rainbow-NDA) provides 26 to 324 percent improvements in the application performance, as well as 26 percent higher average CPU - tilization than traditional service computing framework, in which applications use exclusive servers. The two-tiered on-demand resource allocation further improves performance by 9 to 16 percent for those critical applications, 75 percent of the maximum performance improvement, introducing up to 5 percent performance degradations to others, with 1 to 5 percent improvements in the resource utilization in comparison with Rainbow-NDA. 7. A Decentralized Service Discovery Approach on Peer-to-Peer Networks ABSTRACT: Service-Oriented Computing (SOC) is emerging as a paradigm for developing distributed applications. A critical issue of utilizing SOC is to have a scalable, reliable, and robust service discovery mechanism. However, traditional service discovery methods using centralized registries can easily suffer from problems such as performance bottleneck and vulnerability to failures in large scalable service networks, thus functioning abnormally. To address these problems, this paper proposes a peer-to-peer-based decentralized service discovery approach named Chord4S. Chord4S utilizes the data distribution and lookup capabilities of the popular Chord to distribute and discover services in a decentralized manner. Data availability is further improved by distributing
  • 64. IEEE- Project Title 2013 64 33,Meenakshi Sundaram Building, Sivaji st, (Near Tnagar Bus Terminus),TNagar Chennai-17, Ph: 044-42070551 Mobile: 9025439777/ www.sybiantechnologies.com / sybianprojects@gmail.com published descriptions of functionally equivalent services to different successor nodes that are organized into virtual segments in the Chord4S circle. Based on the service publication approach, Chord4S supports QoS-aware service discovery. Chord4S also supports service discovery with wildcard(s). In addition, the Chord routing protocol is extended to support efficient discovery of multiple services with a single query. This enables late negotiation of Service Level Agreements (SLAs) between service consumers and multiple candidate service providers. The experimental evaluation shows that Chord4S achieves higher data availability and provides efficient query with reasonable overhead.
  • 65. IEEE- Project Title 2013 65 33,Meenakshi Sundaram Building, Sivaji st, (Near Tnagar Bus Terminus),TNagar Chennai-17, Ph: 044-42070551 Mobile: 9025439777/ www.sybiantechnologies.com / sybianprojects@gmail.com SOFTWARE ENGINEERING 1. Ranking and Clustering Software Cost Estimation Models through a Multiple Comparisons Algorithm ABSTRACT: Software Cost Estimation can be described as the process of predicting the most realistic effort required to complete a software project. Due to the strong relationship of accurate effort estimations with many crucial project management activities, the research community has been focused on the development and application of a vast variety of methods and models trying to improve the estimation procedure. From the diversity of methods emerged the need for comparisons to determine the best model. However, the inconsistent results brought to light significant doubts and uncertainty about the appropriateness of the comparison process in experimental studies. Overall, there exist several potential sources of bias that have to be considered in order to reinforce the confidence of experiments. In this paper, we propose a statistical framework based on a multiple comparisons algorithm in order to rank several cost estimation models, identifying those which have significant differences in accuracy, and clustering them in nonoverlapping groups. The proposed framework is applied in a large-scale setup of comparing 11 prediction models over six datasets. The results illustrate the benefits and the significant information obtained through the systematic comparison of alternative methods.
  • 66. IEEE- Project Title 2013 66 33,Meenakshi Sundaram Building, Sivaji st, (Near Tnagar Bus Terminus),TNagar Chennai-17, Ph: 044-42070551 Mobile: 9025439777/ www.sybiantechnologies.com / sybianprojects@gmail.com 2. Reducing Features to Improve Code Change-Based Bug Prediction ABSTRACT: Machine learning classifiers have recently emerged as a way to predict the introduction of bugs in changes made to source code files. The classifier is first trained on software history, and then used to predict if an impending change causes a bug. Drawbacks of existing classifier-based bug prediction techniques are insufficient performance for practical use and slow prediction times due to a large number of machine learned features. This paper investigates multiple feature selection techniques that are generally applicable to classification-based bug prediction methods. The techniques discard less important features until optimal classification performance is reached. The total number of features used for training is substantially reduced, often to less than 10 percent of the original. The performance of Naive Bayes and Support Vector Machine (SVM) classifiers when using this technique is characterized on 11 software projects. Naive Bayes using feature selection provides significant improvement in buggy F-measure (21 percent improvement) over prior change classification bug prediction results (by the second and fourth authors [28]). The SVM's improvement in buggy F-measure is 9 percent. Interestingly, an analysis of performance for varying numbers of features shows that strong performance is achieved at even 1 percent of the original number of features.
  • 67. IEEE- Project Title 2013 67 33,Meenakshi Sundaram Building, Sivaji st, (Near Tnagar Bus Terminus),TNagar Chennai-17, Ph: 044-42070551 Mobile: 9025439777/ www.sybiantechnologies.com / sybianprojects@gmail.com 3. Ant Colony Optimization for Software Project Scheduling and Staffing with an Event-Based Scheduler ABSTRACT: Research into developing effective computer aided techniques for planning software projects is important and challenging for software engineering. Different from projects in other fields, software projects are people-intensive activities and their related resources are mainly human resources. Thus, an adequate model for software project planning has to deal with not only the problem of project task scheduling but also the problem of human resource allocation. But as both of these two problems are difficult, existing models either suffer from a very large search space or have to restrict the flexibility of human resource allocation to simplify the model. To develop a flexible and effective model for software project planning, this paper develops a novel approach with an event-based scheduler (EBS) and an ant colony optimization (ACO) algorithm. The proposed approach represents a plan by a task list and a planned employee allocation matrix. In this way, both the issues of task scheduling and employee allocation can be taken into account. In the EBS, the beginning time of the project, the time when resources are released from finished tasks, and the time when employees join or leave the project are regarded as events. The basic idea of the EBS is to adjust the allocation of employees at events and keep the allocation unchanged at nonevents. With this strategy, the proposed method enables the modeling of resource conflict and task preemption and preserves the flexibility in human resource allocation. To solve the planning
  • 68. IEEE- Project Title 2013 68 33,Meenakshi Sundaram Building, Sivaji st, (Near Tnagar Bus Terminus),TNagar Chennai-17, Ph: 044-42070551 Mobile: 9025439777/ www.sybiantechnologies.com / sybianprojects@gmail.com problem, an ACO algorithm is further designed. Experimental results on 83 instances demonstrate that the proposed method is very promising. 4. Locating Need-to-Externalize Constant Strings for Software Internationalization with Generalized String-Taint Analysis ABSTRACT: Nowadays, a software product usually faces a global market. To meet the requirements of different local users, the software product must be internationalized. In an internationalized software product, user-visible hard-coded constant strings are externalized to resource files so that local versions can be generated by translating the resource files. In many cases, a software product is not internationalized at the beginning of the software development process. To internationalize an existing product, the developers must locate the user-visible constant strings that should be externalized. This locating process is tedious and error-prone due to 1) the large number of both user-visible and non-user-visible constant strings and 2) the complex data flows from constant strings to the Graphical User Interface (GUI). In this paper, we propose an automatic approach to locating need-to-externalize constant strings in the source code of a software product. Given a list of precollected API methods that output values of their string argument variables to the GUI and the source code of the software product under analysis, our approach traces from the invocation sites (within the source code) of these methods back to the need-to-externalize constant strings using generalized string-taint analysis. In our empirical evaluation, we used our approach to locate need-to-externalize constant strings in the uninternationalized versions of seven
  • 69. IEEE- Project Title 2013 69 33,Meenakshi Sundaram Building, Sivaji st, (Near Tnagar Bus Terminus),TNagar Chennai-17, Ph: 044-42070551 Mobile: 9025439777/ www.sybiantechnologies.com / sybianprojects@gmail.com real-world open source software products. The results of our evaluation demonstrate that our approach is able to effectively locate need-to-externalize constant strings in uninternationalized software products. Furthermore, to help developers understand why a constant string requires translation and properly translate the need-to-externalize strings, we provide visual representation of the string dependencies related to the need-to-externalize strings.

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