In recent years, web services run by big corporations and different application-specific data centers have all been embraced by several companies worldwide. Web services provide several benefits when compared to other communication technologies. However, it still suffers from congestion and bottlenecks as well as a significant delay due to the tremendous load caused by a large number of web service requests from end users. Clustering and then aggregating similar web services as one compressed message can potentially achieve network traffic reduction. This paper proposes a dynamic Hilbert clustering as a new model for clustering web services based on convex set similarity. Mathematically, the suggested models compute the degree of similarity between simple object access protocol (SOAP) messages and then cluster them into groups with high similarity. Next, each cluster is aggregated as a compact message that is finally encoded by fixed-length or Huffman. The experiment results have shown the suggested model performs better than the conventional clustering techniques in terms of compression ratio. The suggested model has produced the best results, reaching up to 15 with fixed-length and up to 20 with Huffman
AN OPEN JACKSON NETWORK MODEL FOR HETEROGENEOUS INFRASTRUCTURE AS A SERVICE O...IJCNCJournal
Cloud computing is an environment which provides services for user demand such as software, platform, infrastructure. Applications which are deployed on cloud computing have become more varied and complex to adapt to increase end-user quantity and fluctuating workload. One popular characteristic of
cloud computing is the heterogeneity of network, hosts and virtual machines (VM). There were many studies on cloud computing modeling based on queuing theory, but most studies have focused on homogeneity characteristic. In this study, we propose a cloud computing model based on open Jackson
network for multi-tier application systems which are deployed on heterogeneous VMs of IaaS cloud computing. The important metrics are analyzed in our experiments such as mean waiting time; mean request quantity, the throughput of the system. Besides that, metrics in model is used to modify number VMs
allocated for applications. Result of experiments shows that open queue network provides high efficiency.
Fast Distribution of Replicated Content to Multi- Homed ClientsIDES Editor
Clients can potentially have access to more than
one communication network nowadays due to the availability
of a wide variety of access technologies. On the other hand,
service replication has become a trivial approach in overlay
networks to provide a high availability of data and better QoS.
In this paper, we consider such a multi-homed client seeking
a replicated service in overlay network (e.g., CDN, peer-topeer).
Our aim is to improve the content distribution by
proposing a new model for being applied at the applicationlevel
and in a fully distributed way. Basically, our model
proposes to determine the best mirror server that could be
reached through each client’s network interface based on
application utility function. Then, it consists of downloading
the requested content from the determined best servers
simultaneously through their associated interfaces. Each best
server should deliver a specific estimated range of bytes (i.e.,
content chunk) to an independent TCP socket opened at the
client side for being finally aggregated at the applicationlevel.
Our real experiments show that our model is able to
considerably improve the QoS (e.g., content transfer time)
perceived by the client comparing to the traditional content
distribution techniques.
PROPOSED LOAD BALANCING ALGORITHM TO REDUCE RESPONSE TIME AND PROCESSING TIME...IJCNCJournal
Cloud computing is a new technology that brings new challenges to all organizations around the world.
Improving response time for user requests on cloud computing is a critical issue to combat bottlenecks. As
for cloud computing, bandwidth to from cloud service providers is a bottleneck. With the rapid development
of the scale and number of applications, this access is often threatened by overload. Therefore, this paper
our proposed Throttled Modified Algorithm(TMA) for improving the response time of VMs on cloud
computing to improve performance for end-user. We have simulated the proposed algorithm with the
CloudAnalyts simulation tool and this algorithm has improved response times and processing time of the
cloud data center.
On the Optimal Allocation of VirtualResources in Cloud Compu.docxhopeaustin33688
On the Optimal Allocation of Virtual
Resources in Cloud Computing Networks
Chrysa Papagianni, Aris Leivadeas, Symeon Papavassiliou,
Vasilis Maglaris, Cristina Cervelló-Pastor, and �Alvaro Monje
Abstract—Cloud computing builds upon advances on virtualization and distributed computing to support cost-efficient usage of
computing resources, emphasizing on resource scalability and on demand services. Moving away from traditional data-center oriented
models, distributed clouds extend over a loosely coupled federated substrate, offering enhanced communication and computational
services to target end-users with quality of service (QoS) requirements, as dictated by the future Internet vision. Toward facilitating the
efficient realization of such networked computing environments, computing and networking resources need to be jointly treated and
optimized. This requires delivery of user-driven sets of virtual resources, dynamically allocated to actual substrate resources within
networked clouds, creating the need to revisit resource mapping algorithms and tailor them to a composite virtual resource mapping
problem. In this paper, toward providing a unified resource allocation framework for networked clouds, we first formulate the optimal
networked cloud mapping problem as a mixed integer programming (MIP) problem, indicating objectives related to cost efficiency of
the resource mapping procedure, while abiding by user requests for QoS-aware virtual resources. We subsequently propose a method
for the efficient mapping of resource requests onto a shared substrate interconnecting various islands of computing resources, and
adopt a heuristic methodology to address the problem. The efficiency of the proposed approach is illustrated in a simulation/emulation
environment, that allows for a flexible, structured, and comparative performance evaluation. We conclude by outlining a proof-of-
concept realization of our proposed schema, mounted over the European future Internet test-bed FEDERICA, a resource virtualization
platform augmented with network and computing facilities.
Index Terms—Federated infrastructures, resource allocation, resource mapping, virtualization, cloud computing, quality of service
Ç
1 INTRODUCTION
CLOUD computing promises reliable services deliveredthrough next generation data centers that are built on
compute and storage virtualization technologies. According
to Buyya et al., [1] “a cloud is a type of parallel and distributed
system consisting of a collection of interconnected and virtualized
computers that are dynamically provisioned and presented as one
or more unified computing resources based on service-level
agreements established through negotiation between the service
provider and the consumers” and accessible as a composable
service via web 2.0 technologies.
Therefore, with respect to cloud computing there exist
the “as a service” definitions, which include software as a
service (SaaS), infrastructure as a se.
International Journal of Engineering Research and Development (IJERD)IJERD Editor
journal publishing, how to publish research paper, Call For research paper, international journal, publishing a paper, IJERD, journal of science and technology, how to get a research paper published, publishing a paper, publishing of journal, publishing of research paper, reserach and review articles, IJERD Journal, How to publish your research paper, publish research paper, open access engineering journal, Engineering journal, Mathemetics journal, Physics journal, Chemistry journal, Computer Engineering, Computer Science journal, how to submit your paper, peer reviw journal, indexed journal, reserach and review articles, engineering journal, www.ijerd.com, research journals,
yahoo journals, bing journals, International Journal of Engineering Research and Development, google journals, hard copy of journal
An Efficient Queuing Model for Resource Sharing in Cloud Computingtheijes
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
The papers for publication in The International Journal of Engineering& Science are selected through rigorous peer reviews to ensure originality, timeliness, relevance, and readability.
A combined computing framework for load balancing in multi-tenant cloud eco-...IJECEIAES
Since the world is getting digitalized, cloud computing has become a core part of it. Massive data on a daily basis is processed, stored, and transferred over the internet. Cloud computing has become quite popular because of its superlative quality and enhanced capability to improvise data management, offering better computing resources and data to its user bases (UBs). However, there are many issues in the existing cloud traffic management approaches and how to manage data during service execution. The study introduces two distinct research models: data center virtualization framework under multi-tenant cloud-ecosystem (DCVF-MT) and collaborative workflow of multi-tenant load balancing (CW-MTLB) with analytical research modeling. The sequence of execution flow considers a set of algorithms for both models that address the core problem of load balancing and resource allocation in the cloud computing (CC) ecosystem. The research outcome illustrates that DCVF-MT, outperforms the one-toone approach by approximately 24.778% performance improvement in traffic scheduling. It also yields a 40.33% performance improvement in managing cloudlet handling time. Moreover, it attains an overall 8.5133% performance improvement in resource cost optimization, which is significant to ensure the adaptability of the frameworks into futuristic cloud applications where adequate virtualization and resource mapping will be required.
AN OPEN JACKSON NETWORK MODEL FOR HETEROGENEOUS INFRASTRUCTURE AS A SERVICE O...IJCNCJournal
Cloud computing is an environment which provides services for user demand such as software, platform, infrastructure. Applications which are deployed on cloud computing have become more varied and complex to adapt to increase end-user quantity and fluctuating workload. One popular characteristic of
cloud computing is the heterogeneity of network, hosts and virtual machines (VM). There were many studies on cloud computing modeling based on queuing theory, but most studies have focused on homogeneity characteristic. In this study, we propose a cloud computing model based on open Jackson
network for multi-tier application systems which are deployed on heterogeneous VMs of IaaS cloud computing. The important metrics are analyzed in our experiments such as mean waiting time; mean request quantity, the throughput of the system. Besides that, metrics in model is used to modify number VMs
allocated for applications. Result of experiments shows that open queue network provides high efficiency.
Fast Distribution of Replicated Content to Multi- Homed ClientsIDES Editor
Clients can potentially have access to more than
one communication network nowadays due to the availability
of a wide variety of access technologies. On the other hand,
service replication has become a trivial approach in overlay
networks to provide a high availability of data and better QoS.
In this paper, we consider such a multi-homed client seeking
a replicated service in overlay network (e.g., CDN, peer-topeer).
Our aim is to improve the content distribution by
proposing a new model for being applied at the applicationlevel
and in a fully distributed way. Basically, our model
proposes to determine the best mirror server that could be
reached through each client’s network interface based on
application utility function. Then, it consists of downloading
the requested content from the determined best servers
simultaneously through their associated interfaces. Each best
server should deliver a specific estimated range of bytes (i.e.,
content chunk) to an independent TCP socket opened at the
client side for being finally aggregated at the applicationlevel.
Our real experiments show that our model is able to
considerably improve the QoS (e.g., content transfer time)
perceived by the client comparing to the traditional content
distribution techniques.
PROPOSED LOAD BALANCING ALGORITHM TO REDUCE RESPONSE TIME AND PROCESSING TIME...IJCNCJournal
Cloud computing is a new technology that brings new challenges to all organizations around the world.
Improving response time for user requests on cloud computing is a critical issue to combat bottlenecks. As
for cloud computing, bandwidth to from cloud service providers is a bottleneck. With the rapid development
of the scale and number of applications, this access is often threatened by overload. Therefore, this paper
our proposed Throttled Modified Algorithm(TMA) for improving the response time of VMs on cloud
computing to improve performance for end-user. We have simulated the proposed algorithm with the
CloudAnalyts simulation tool and this algorithm has improved response times and processing time of the
cloud data center.
On the Optimal Allocation of VirtualResources in Cloud Compu.docxhopeaustin33688
On the Optimal Allocation of Virtual
Resources in Cloud Computing Networks
Chrysa Papagianni, Aris Leivadeas, Symeon Papavassiliou,
Vasilis Maglaris, Cristina Cervelló-Pastor, and �Alvaro Monje
Abstract—Cloud computing builds upon advances on virtualization and distributed computing to support cost-efficient usage of
computing resources, emphasizing on resource scalability and on demand services. Moving away from traditional data-center oriented
models, distributed clouds extend over a loosely coupled federated substrate, offering enhanced communication and computational
services to target end-users with quality of service (QoS) requirements, as dictated by the future Internet vision. Toward facilitating the
efficient realization of such networked computing environments, computing and networking resources need to be jointly treated and
optimized. This requires delivery of user-driven sets of virtual resources, dynamically allocated to actual substrate resources within
networked clouds, creating the need to revisit resource mapping algorithms and tailor them to a composite virtual resource mapping
problem. In this paper, toward providing a unified resource allocation framework for networked clouds, we first formulate the optimal
networked cloud mapping problem as a mixed integer programming (MIP) problem, indicating objectives related to cost efficiency of
the resource mapping procedure, while abiding by user requests for QoS-aware virtual resources. We subsequently propose a method
for the efficient mapping of resource requests onto a shared substrate interconnecting various islands of computing resources, and
adopt a heuristic methodology to address the problem. The efficiency of the proposed approach is illustrated in a simulation/emulation
environment, that allows for a flexible, structured, and comparative performance evaluation. We conclude by outlining a proof-of-
concept realization of our proposed schema, mounted over the European future Internet test-bed FEDERICA, a resource virtualization
platform augmented with network and computing facilities.
Index Terms—Federated infrastructures, resource allocation, resource mapping, virtualization, cloud computing, quality of service
Ç
1 INTRODUCTION
CLOUD computing promises reliable services deliveredthrough next generation data centers that are built on
compute and storage virtualization technologies. According
to Buyya et al., [1] “a cloud is a type of parallel and distributed
system consisting of a collection of interconnected and virtualized
computers that are dynamically provisioned and presented as one
or more unified computing resources based on service-level
agreements established through negotiation between the service
provider and the consumers” and accessible as a composable
service via web 2.0 technologies.
Therefore, with respect to cloud computing there exist
the “as a service” definitions, which include software as a
service (SaaS), infrastructure as a se.
International Journal of Engineering Research and Development (IJERD)IJERD Editor
journal publishing, how to publish research paper, Call For research paper, international journal, publishing a paper, IJERD, journal of science and technology, how to get a research paper published, publishing a paper, publishing of journal, publishing of research paper, reserach and review articles, IJERD Journal, How to publish your research paper, publish research paper, open access engineering journal, Engineering journal, Mathemetics journal, Physics journal, Chemistry journal, Computer Engineering, Computer Science journal, how to submit your paper, peer reviw journal, indexed journal, reserach and review articles, engineering journal, www.ijerd.com, research journals,
yahoo journals, bing journals, International Journal of Engineering Research and Development, google journals, hard copy of journal
An Efficient Queuing Model for Resource Sharing in Cloud Computingtheijes
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
The papers for publication in The International Journal of Engineering& Science are selected through rigorous peer reviews to ensure originality, timeliness, relevance, and readability.
A combined computing framework for load balancing in multi-tenant cloud eco-...IJECEIAES
Since the world is getting digitalized, cloud computing has become a core part of it. Massive data on a daily basis is processed, stored, and transferred over the internet. Cloud computing has become quite popular because of its superlative quality and enhanced capability to improvise data management, offering better computing resources and data to its user bases (UBs). However, there are many issues in the existing cloud traffic management approaches and how to manage data during service execution. The study introduces two distinct research models: data center virtualization framework under multi-tenant cloud-ecosystem (DCVF-MT) and collaborative workflow of multi-tenant load balancing (CW-MTLB) with analytical research modeling. The sequence of execution flow considers a set of algorithms for both models that address the core problem of load balancing and resource allocation in the cloud computing (CC) ecosystem. The research outcome illustrates that DCVF-MT, outperforms the one-toone approach by approximately 24.778% performance improvement in traffic scheduling. It also yields a 40.33% performance improvement in managing cloudlet handling time. Moreover, it attains an overall 8.5133% performance improvement in resource cost optimization, which is significant to ensure the adaptability of the frameworks into futuristic cloud applications where adequate virtualization and resource mapping will be required.
Evaluation of load balancing approaches for Erlang concurrent application in ...TELKOMNIKA JOURNAL
Cloud system accommodates the computing environment including PaaS (platform as a service), SaaS (software as a service), and IaaS (infrastructure as service) that enables the services of cloud systems. Cloud system allows multiple users to employ computing services through browsers, which reflects an alternative service model that alters the local computing workload to a distant site. Cloud virtualization is another characteristic of the clouds that deliver virtual computing services and imitate the functionality of physical computing resources. It refers to an elastic load balancing management that provides the flexible model of on-demand services. The virtualization allows organizations to improve high levels of reliability, accessibility, and scalability by having a capability to execute applications on multiple resources simultaneously. In this paper we use a queuing model to consider a flexible load balancing and evaluate performance metrics such as mean queue length, throughput, mean waiting time, utilization, and mean traversal time. The model is aware of the arrival of concurrent applications with an Erlang distribution. Simulation results regarding performance metrics are investigated. Results point out that in Cloud systems both the fairness and load balancing are to be significantly considered.
AWSQ: an approximated web server queuing algorithm for heterogeneous web serv...IJECEIAES
With the rising popularity of web-based applications, the primary and consistent resource in the infrastructure of World Wide Web are cluster-based web servers. Overtly in dynamic contents and database driven applications, especially at heavy load circumstances, the performance handling of clusters is a solemn task. Without using efficient mechanisms, an overloaded web server cannot provide great performance. In clusters, this overloaded condition can be avoided using load balancing mechanisms by sharing the load among available web servers. The existing load balancing mechanisms which were intended to handle static contents will grieve from substantial performance deprivation under database-driven and dynamic contents. The most serviceable load balancing approaches are Web Server Queuing (WSQ), Server Content based Queue (QSC) and Remaining Capacity (RC) under specific conditions to provide better results. By Considering this, we have proposed an approximated web server Queuing mechanism for web server clusters and also proposed an analytical model for calculating the load of a web server. The requests are classified based on the service time and keep tracking the number of outstanding requests at each webserver to achieve better performance. The approximated load of each web server is used for load balancing. The investigational results illustrate the effectiveness of the proposed mechanism by improving the mean response time, throughput and drop rate of the server cluster.
Multi-objective tasks scheduling using bee colony algorithm in cloud computingIJECEIAES
Due to the development of communication device technology and the need to use up-to-date infrastructure ready to respond quickly and in a timely manner to computational needs, the competition for the use of processing resources is increasing nowadays. The scheduling tasks in the cloud computing environment have been remained a challenge to access a quick and efficient solution. In this paper, the aim is to present a new tactic for allocating the available processing resources based on the artificial bee colony (ABC) algorithm and cellular automata for solving the task scheduling problem in the cloud computing network. The results show the performance of the proposed method is better than its counterparts.
Cost-Minimizing Dynamic Migration of Content Distribution Services into Hybri...1crore projects
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5. IEEE based on Multimedia
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Java Project Domain list 2015
1. IEEE based on datamining and knowledge engineering
2. IEEE based on mobile computing
3. IEEE based on networking
4. IEEE based on Image processing
5. IEEE based on Multimedia
6. IEEE based on Network security
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An approximation delay between consecutive requests for congestion control in...IJECEIAES
This research presents a way to avoid network congestion during unicast CoAP-based group communication using increased delays between consecutive requests (DCR) in LoWPAN border routers to limit request send rates. It also provides a way to determine DCR values that are suitable for various network group sizes with differing node counts. The optimal DCR is obtained using the least squares approximation method and the relative minimum. Results from experimentation shows a positive relation, that is, an increase in group size necessitates an increase in DCR value. Experiments in various group sizes show favorable network performance and support the proposed congestion control method using DCR.
ESTIMATING CLOUD COMPUTING ROUND-TRIP TIME (RTT) USING FUZZY LOGIC FOR INTERR...IJCI JOURNAL
Cloud computing is widely considered a transformative force in the computing world and is poised to
replace the traditional office setup as an industry standard. However, given the relative novelty of these
services and challenges such as the impact of physical distance on round-trip time (rtt), questions have
arisen regarding system performance and associated billing structures. The primary objective of this study
is to address these concerns. We aim to alleviate doubts by leveraging a fuzzy logic system to classify
distances between regions that support computing services and compare them with the conventional web
hosting format. To achieve this, we analyse the responses of one of these services, like amazon web
services, across different distance categories (near, medium, and far) between regions and strive to
conclude overall system performance. Our tests reveal that significant data is consistently lost during
customer transmission despite exhibiting superior round-trip times. We delve into this issue and present
our findings, which may illuminate the observed anomalous behaviour.
THE DEVELOPMENT AND STUDY OF THE METHODS AND ALGORITHMS FOR THE CLASSIFICATIO...IJCNCJournal
This paper represents the results of the research, which have allowed us to develop a hybrid
approach to the processing, classification, and control of traffic routes. The approach enables to
identify traffic flows in the virtual data center in real-time systems. Our solution is based on the
methods of data mining and machine learning, which enable to classify traffic more accurately
according to more criteria and parameters. As a practical result, the paper represents the
algorithmic solution of the classification of the traffic flows of cloud applications and services
embodied in a module for the controller of the software-defined network. This solution enables to
increase the efficiency of handling user requests to cloud applications and reduce the response
time, which has a positive effect on the quality of service in the network of the virtual data center
Agent based Aggregation of Cloud Services- A Research Agendaidescitation
-Cloud computing has come to the forefront as it
overcomes some of the issues in computing such as storage
space and processing power. It enables ubiquitous accessing
and processing of information without the need of excessive
computing facilities. In this work, we plan to brief some of the
issues in aggregating the cloud services, discovering futuristic
cloud service requests, develop a repository of the same and
propose an agent based Quality of Service (QoS) provisioning
system for cloud clients.
Optimization and Evaluation of a Multimedia Streaming Service on Hybrid Telco...ijccsa
With recent developments in cloud computing, a paradigm shift from rather static deployment of resources to more dynamic, on-demand practices means more flexibility and better utilization of resources. This demands new ways to efficiently configure networks. In this paper, we will characterize a class of competitive cloud services that telecom operators could provide based on the characteristics of telecom infrastructure through an applicable streaming service architecture. Then, we will model this architecture as a cost-based mathematic model. This model provides a tool to evaluate and compare the cost of software services for different telecom network topologies and deployment strategies. Additionally, with each topology it acts as a means to characterize the deployment solution that yields the lowest resource usage over the entire network. These applications are illustrated through numerical analysis. Finally, a proof-of-concept prototype is deployed to shows dynamic properties of the service in the architecture and the model above
Management of context aware software resources deployed in a cloud environmen...ijdpsjournal
In cloud computing environments, context information is continuously created by context providers and
consumed by the applications on mobile devices. An important characteristic of cloud-based context aware
services is meeting the service level agreements (SLAs) to deliver a certain quality of service (Qos), such as
guarantees on response time or price. The response time to a request of context-aware software is affected
by loading extensive context data from multiple resources on the chosen server. Therefore, the speed of
such software would be decreased during execution time. Hence, proper scheduling of such services is
indispensable because the customers are faced with time constraints. In this research, a new scheduling
algorithm for context aware services is proposed which is based on classifying similar context consumers
and dynamically scoring the requests to improve the performance of the server hosting highly-requested
context-aware software while reducing costs of cloud provider. The approach is evaluated via simulation
and comparison with gi-FIFO scheduling algorithm. Experimental results demonstrate the efficiency of the
proposed approach.
A latency-aware max-min algorithm for resource allocation in cloud IJECEIAES
Cloud computing is an emerging distributed computing paradigm. However, it requires certain initiatives that need to be tailored for the cloud environment such as the provision of an on-the-fly mechanism for providing resource availability based on the rapidly changing demands of the customers. Although, resource allocation is an important problem and has been widely studied, there are certain criteria that need to be considered. These criteria include meeting user’s quality of service (QoS) requirements. High QoS can be guaranteed only if resources are allocated in an optimal manner. This paper proposes a latency-aware max-min algorithm (LAM) for allocation of resources in cloud infrastructures. The proposed algorithm was designed to address challenges associated with resource allocation such as variations in user demands and on-demand access to unlimited resources. It is capable of allocating resources in a cloud-based environment with the target of enhancing infrastructure-level performance and maximization of profits with the optimum allocation of resources. A priority value is also associated with each user, which is calculated by analytic hierarchy process (AHP). The results validate the superiority for LAM due to better performance in comparison to other state-of-the-art algorithms with flexibility in resource allocation for fluctuating resource demand patterns.
MCCVA: A NEW APPROACH USING SVM AND KMEANS FOR LOAD BALANCING ON CLOUDijccsa
Nowadays, the demand of using resources, using services via the intranet system or on the Internet is rapidly growing. The respective problem coming is how to use these resources effectively in terms of time and quality. Therefore, the network QoS and its economy are people concerns, cloud computing was born in an inevitable trend. However, managing resources and scheduling tasks in virtualized data centres on the cloud are challenging tasks. Currently, there are a lot of Load Balancing algorithms applied in clouds and proposed by many authors, scholars, and experts. These existing methods are more about natural and heuristic, but the application of AI, or modern datamining technologies, in load balancing is not too popular due to the different characteristics of cloud. In this paper, we propose an algorithm to reduce the processing time (makespan) on cloud computing, helping the load balancing work more efficiency. Here, we use the SVM algorithm to classify the coming Requests, K - Mean to cluster the VMs in cloud, then the LB will allocate the requests into the VMs in the most reasonable way. In this way, request with the least processing time will be allocated to the VMs with the lowest usage. We name this new proposal as MCCVA - Makespan Classification & Clustering VM Algorithm. We have experimented and evaluated this algorithm in CloudSim, a cloud simulation environment, we obtained better results than some other wellknown algorithms. With this MCCVA, we can see the big potential of AI and datamining in Load Balancing, we can further develop LB with AI to achieve better and better results of QoS.
LOAD BALANCING ALGORITHM ON CLOUD COMPUTING FOR OPTIMIZE RESPONE TIMEijccsa
To improve the performance of cloud computing, there are many parameters and issues that we should consider, including resource allocation, resource responsiveness, connectivity to resources, unused resources exploration, corresponding resource mapping and planning for resource. The planning for the use of resources can be based on many kinds of parameters, and the service response time is one of them.
The users can easily figure out the response time of their requests, and it becomes one of the important QoSs. When we discover and explore more on this, response time can provide solutions for the distribution, the load balancing of resources with better efficiency. This is one of the most promising
research directions for improving the cloud technology. Therefore, this paper proposes a load balancing algorithm based on response time of requests on cloud with the name APRA (ARIMA Prediction of Response Time Algorithm), the main idea is to use ARIMA algorithms to predict the coming response time, thus giving a better way of effectively resolving resource allocation with threshold value. The experiment
result outcomes are potential and valuable for load balancing with predicted response time, it shows that prediction is a great direction for load balancing.
Traffic-aware adaptive server load balancing for softwaredefined networks IJECEIAES
Servers in data center networks handle heterogeneous bulk loads. Load balancing, therefore, plays an important role in optimizing network bandwidth and minimizing response time. A complete knowledge of the current network status is needed to provide a stable load in the network. The process of network status catalog in a traditional network needs additional processing which increases complexity, whereas, in software defined networking, the control plane monitors the overall working of the network continuously. Hence it is decided to propose an efficient load balancing algorithm that adapts SDN. This paper proposes an efficient algorithm TAASLB-traffic-aware adaptive server load balancing to balance the flows to the servers in a data center network. It works based on two parameters, residual bandwidth, and server capacity. It detects the elephant flows and forwards them towards the optimal server where it can be processed quickly. It has been tested with the Mininet simulator and gave considerably better results compared to the existing server load balancing algorithms in the floodlight controller. After experimentation and analysis, it is understood that the method provides comparatively better results than the existing load balancing algorithms.
Technical analysis of content placement algorithms for content delivery netwo...IJECEIAES
Content placement algorithm is an integral part of the cloud-based content de-livery network. They are responsible for selecting a precise content to be re-posited over the surrogate servers distributed over a geographical region. Although various works are being already carried out in this sector, there are loopholes connected to most of the work, which doesn't have much disclosure. It is already known that quality of service, quality of experience, and the cost is always an essential objective targeting to be improved in existing work. Still, there are various other aspects and underlying reasons which are equally important from the design aspect. Therefore, this paper contributes towards reviewing the existing approaches of content placement algorithm over cloud-based content delivery network targeting to explore open-end re-search issues.
Bibliometric analysis highlighting the role of women in addressing climate ch...IJECEIAES
Fossil fuel consumption increased quickly, contributing to climate change
that is evident in unusual flooding and draughts, and global warming. Over
the past ten years, women's involvement in society has grown dramatically,
and they succeeded in playing a noticeable role in reducing climate change.
A bibliometric analysis of data from the last ten years has been carried out to
examine the role of women in addressing the climate change. The analysis's
findings discussed the relevant to the sustainable development goals (SDGs),
particularly SDG 7 and SDG 13. The results considered contributions made
by women in the various sectors while taking geographic dispersion into
account. The bibliometric analysis delves into topics including women's
leadership in environmental groups, their involvement in policymaking, their
contributions to sustainable development projects, and the influence of
gender diversity on attempts to mitigate climate change. This study's results
highlight how women have influenced policies and actions related to climate
change, point out areas of research deficiency and recommendations on how
to increase role of the women in addressing the climate change and
achieving sustainability. To achieve more successful results, this initiative
aims to highlight the significance of gender equality and encourage
inclusivity in climate change decision-making processes.
Voltage and frequency control of microgrid in presence of micro-turbine inter...IJECEIAES
The active and reactive load changes have a significant impact on voltage
and frequency. In this paper, in order to stabilize the microgrid (MG) against
load variations in islanding mode, the active and reactive power of all
distributed generators (DGs), including energy storage (battery), diesel
generator, and micro-turbine, are controlled. The micro-turbine generator is
connected to MG through a three-phase to three-phase matrix converter, and
the droop control method is applied for controlling the voltage and
frequency of MG. In addition, a method is introduced for voltage and
frequency control of micro-turbines in the transition state from gridconnected mode to islanding mode. A novel switching strategy of the matrix
converter is used for converting the high-frequency output voltage of the
micro-turbine to the grid-side frequency of the utility system. Moreover,
using the switching strategy, the low-order harmonics in the output current
and voltage are not produced, and consequently, the size of the output filter
would be reduced. In fact, the suggested control strategy is load-independent
and has no frequency conversion restrictions. The proposed approach for
voltage and frequency regulation demonstrates exceptional performance and
favorable response across various load alteration scenarios. The suggested
strategy is examined in several scenarios in the MG test systems, and the
simulation results are addressed.
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Cloud system accommodates the computing environment including PaaS (platform as a service), SaaS (software as a service), and IaaS (infrastructure as service) that enables the services of cloud systems. Cloud system allows multiple users to employ computing services through browsers, which reflects an alternative service model that alters the local computing workload to a distant site. Cloud virtualization is another characteristic of the clouds that deliver virtual computing services and imitate the functionality of physical computing resources. It refers to an elastic load balancing management that provides the flexible model of on-demand services. The virtualization allows organizations to improve high levels of reliability, accessibility, and scalability by having a capability to execute applications on multiple resources simultaneously. In this paper we use a queuing model to consider a flexible load balancing and evaluate performance metrics such as mean queue length, throughput, mean waiting time, utilization, and mean traversal time. The model is aware of the arrival of concurrent applications with an Erlang distribution. Simulation results regarding performance metrics are investigated. Results point out that in Cloud systems both the fairness and load balancing are to be significantly considered.
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With the rising popularity of web-based applications, the primary and consistent resource in the infrastructure of World Wide Web are cluster-based web servers. Overtly in dynamic contents and database driven applications, especially at heavy load circumstances, the performance handling of clusters is a solemn task. Without using efficient mechanisms, an overloaded web server cannot provide great performance. In clusters, this overloaded condition can be avoided using load balancing mechanisms by sharing the load among available web servers. The existing load balancing mechanisms which were intended to handle static contents will grieve from substantial performance deprivation under database-driven and dynamic contents. The most serviceable load balancing approaches are Web Server Queuing (WSQ), Server Content based Queue (QSC) and Remaining Capacity (RC) under specific conditions to provide better results. By Considering this, we have proposed an approximated web server Queuing mechanism for web server clusters and also proposed an analytical model for calculating the load of a web server. The requests are classified based on the service time and keep tracking the number of outstanding requests at each webserver to achieve better performance. The approximated load of each web server is used for load balancing. The investigational results illustrate the effectiveness of the proposed mechanism by improving the mean response time, throughput and drop rate of the server cluster.
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Due to the development of communication device technology and the need to use up-to-date infrastructure ready to respond quickly and in a timely manner to computational needs, the competition for the use of processing resources is increasing nowadays. The scheduling tasks in the cloud computing environment have been remained a challenge to access a quick and efficient solution. In this paper, the aim is to present a new tactic for allocating the available processing resources based on the artificial bee colony (ABC) algorithm and cellular automata for solving the task scheduling problem in the cloud computing network. The results show the performance of the proposed method is better than its counterparts.
Cost-Minimizing Dynamic Migration of Content Distribution Services into Hybri...1crore projects
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Cloud computing is widely considered a transformative force in the computing world and is poised to
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Bibliometric analysis highlighting the role of women in addressing climate ch...IJECEIAES
Fossil fuel consumption increased quickly, contributing to climate change
that is evident in unusual flooding and draughts, and global warming. Over
the past ten years, women's involvement in society has grown dramatically,
and they succeeded in playing a noticeable role in reducing climate change.
A bibliometric analysis of data from the last ten years has been carried out to
examine the role of women in addressing the climate change. The analysis's
findings discussed the relevant to the sustainable development goals (SDGs),
particularly SDG 7 and SDG 13. The results considered contributions made
by women in the various sectors while taking geographic dispersion into
account. The bibliometric analysis delves into topics including women's
leadership in environmental groups, their involvement in policymaking, their
contributions to sustainable development projects, and the influence of
gender diversity on attempts to mitigate climate change. This study's results
highlight how women have influenced policies and actions related to climate
change, point out areas of research deficiency and recommendations on how
to increase role of the women in addressing the climate change and
achieving sustainability. To achieve more successful results, this initiative
aims to highlight the significance of gender equality and encourage
inclusivity in climate change decision-making processes.
Voltage and frequency control of microgrid in presence of micro-turbine inter...IJECEIAES
The active and reactive load changes have a significant impact on voltage
and frequency. In this paper, in order to stabilize the microgrid (MG) against
load variations in islanding mode, the active and reactive power of all
distributed generators (DGs), including energy storage (battery), diesel
generator, and micro-turbine, are controlled. The micro-turbine generator is
connected to MG through a three-phase to three-phase matrix converter, and
the droop control method is applied for controlling the voltage and
frequency of MG. In addition, a method is introduced for voltage and
frequency control of micro-turbines in the transition state from gridconnected mode to islanding mode. A novel switching strategy of the matrix
converter is used for converting the high-frequency output voltage of the
micro-turbine to the grid-side frequency of the utility system. Moreover,
using the switching strategy, the low-order harmonics in the output current
and voltage are not produced, and consequently, the size of the output filter
would be reduced. In fact, the suggested control strategy is load-independent
and has no frequency conversion restrictions. The proposed approach for
voltage and frequency regulation demonstrates exceptional performance and
favorable response across various load alteration scenarios. The suggested
strategy is examined in several scenarios in the MG test systems, and the
simulation results are addressed.
Enhancing battery system identification: nonlinear autoregressive modeling fo...IJECEIAES
Precisely characterizing Li-ion batteries is essential for optimizing their
performance, enhancing safety, and prolonging their lifespan across various
applications, such as electric vehicles and renewable energy systems. This
article introduces an innovative nonlinear methodology for system
identification of a Li-ion battery, employing a nonlinear autoregressive with
exogenous inputs (NARX) model. The proposed approach integrates the
benefits of nonlinear modeling with the adaptability of the NARX structure,
facilitating a more comprehensive representation of the intricate
electrochemical processes within the battery. Experimental data collected
from a Li-ion battery operating under diverse scenarios are employed to
validate the effectiveness of the proposed methodology. The identified
NARX model exhibits superior accuracy in predicting the battery's behavior
compared to traditional linear models. This study underscores the
importance of accounting for nonlinearities in battery modeling, providing
insights into the intricate relationships between state-of-charge, voltage, and
current under dynamic conditions.
Smart grid deployment: from a bibliometric analysis to a surveyIJECEIAES
Smart grids are one of the last decades' innovations in electrical energy.
They bring relevant advantages compared to the traditional grid and
significant interest from the research community. Assessing the field's
evolution is essential to propose guidelines for facing new and future smart
grid challenges. In addition, knowing the main technologies involved in the
deployment of smart grids (SGs) is important to highlight possible
shortcomings that can be mitigated by developing new tools. This paper
contributes to the research trends mentioned above by focusing on two
objectives. First, a bibliometric analysis is presented to give an overview of
the current research level about smart grid deployment. Second, a survey of
the main technological approaches used for smart grid implementation and
their contributions are highlighted. To that effect, we searched the Web of
Science (WoS), and the Scopus databases. We obtained 5,663 documents
from WoS and 7,215 from Scopus on smart grid implementation or
deployment. With the extraction limitation in the Scopus database, 5,872 of
the 7,215 documents were extracted using a multi-step process. These two
datasets have been analyzed using a bibliometric tool called bibliometrix.
The main outputs are presented with some recommendations for future
research.
Use of analytical hierarchy process for selecting and prioritizing islanding ...IJECEIAES
One of the problems that are associated to power systems is islanding
condition, which must be rapidly and properly detected to prevent any
negative consequences on the system's protection, stability, and security.
This paper offers a thorough overview of several islanding detection
strategies, which are divided into two categories: classic approaches,
including local and remote approaches, and modern techniques, including
techniques based on signal processing and computational intelligence.
Additionally, each approach is compared and assessed based on several
factors, including implementation costs, non-detected zones, declining
power quality, and response times using the analytical hierarchy process
(AHP). The multi-criteria decision-making analysis shows that the overall
weight of passive methods (24.7%), active methods (7.8%), hybrid methods
(5.6%), remote methods (14.5%), signal processing-based methods (26.6%),
and computational intelligent-based methods (20.8%) based on the
comparison of all criteria together. Thus, it can be seen from the total weight
that hybrid approaches are the least suitable to be chosen, while signal
processing-based methods are the most appropriate islanding detection
method to be selected and implemented in power system with respect to the
aforementioned factors. Using Expert Choice software, the proposed
hierarchy model is studied and examined.
Enhancing of single-stage grid-connected photovoltaic system using fuzzy logi...IJECEIAES
The power generated by photovoltaic (PV) systems is influenced by
environmental factors. This variability hampers the control and utilization of
solar cells' peak output. In this study, a single-stage grid-connected PV
system is designed to enhance power quality. Our approach employs fuzzy
logic in the direct power control (DPC) of a three-phase voltage source
inverter (VSI), enabling seamless integration of the PV connected to the
grid. Additionally, a fuzzy logic-based maximum power point tracking
(MPPT) controller is adopted, which outperforms traditional methods like
incremental conductance (INC) in enhancing solar cell efficiency and
minimizing the response time. Moreover, the inverter's real-time active and
reactive power is directly managed to achieve a unity power factor (UPF).
The system's performance is assessed through MATLAB/Simulink
implementation, showing marked improvement over conventional methods,
particularly in steady-state and varying weather conditions. For solar
irradiances of 500 and 1,000 W/m2
, the results show that the proposed
method reduces the total harmonic distortion (THD) of the injected current
to the grid by approximately 46% and 38% compared to conventional
methods, respectively. Furthermore, we compare the simulation results with
IEEE standards to evaluate the system's grid compatibility.
Enhancing photovoltaic system maximum power point tracking with fuzzy logic-b...IJECEIAES
Photovoltaic systems have emerged as a promising energy resource that
caters to the future needs of society, owing to their renewable, inexhaustible,
and cost-free nature. The power output of these systems relies on solar cell
radiation and temperature. In order to mitigate the dependence on
atmospheric conditions and enhance power tracking, a conventional
approach has been improved by integrating various methods. To optimize
the generation of electricity from solar systems, the maximum power point
tracking (MPPT) technique is employed. To overcome limitations such as
steady-state voltage oscillations and improve transient response, two
traditional MPPT methods, namely fuzzy logic controller (FLC) and perturb
and observe (P&O), have been modified. This research paper aims to
simulate and validate the step size of the proposed modified P&O and FLC
techniques within the MPPT algorithm using MATLAB/Simulink for
efficient power tracking in photovoltaic systems.
Adaptive synchronous sliding control for a robot manipulator based on neural ...IJECEIAES
Robot manipulators have become important equipment in production lines, medical fields, and transportation. Improving the quality of trajectory tracking for
robot hands is always an attractive topic in the research community. This is a
challenging problem because robot manipulators are complex nonlinear systems
and are often subject to fluctuations in loads and external disturbances. This
article proposes an adaptive synchronous sliding control scheme to improve trajectory tracking performance for a robot manipulator. The proposed controller
ensures that the positions of the joints track the desired trajectory, synchronize
the errors, and significantly reduces chattering. First, the synchronous tracking
errors and synchronous sliding surfaces are presented. Second, the synchronous
tracking error dynamics are determined. Third, a robust adaptive control law is
designed,the unknown components of the model are estimated online by the neural network, and the parameters of the switching elements are selected by fuzzy
logic. The built algorithm ensures that the tracking and approximation errors
are ultimately uniformly bounded (UUB). Finally, the effectiveness of the constructed algorithm is demonstrated through simulation and experimental results.
Simulation and experimental results show that the proposed controller is effective with small synchronous tracking errors, and the chattering phenomenon is
significantly reduced.
Remote field-programmable gate array laboratory for signal acquisition and de...IJECEIAES
A remote laboratory utilizing field-programmable gate array (FPGA) technologies enhances students’ learning experience anywhere and anytime in embedded system design. Existing remote laboratories prioritize hardware access and visual feedback for observing board behavior after programming, neglecting comprehensive debugging tools to resolve errors that require internal signal acquisition. This paper proposes a novel remote embeddedsystem design approach targeting FPGA technologies that are fully interactive via a web-based platform. Our solution provides FPGA board access and debugging capabilities beyond the visual feedback provided by existing remote laboratories. We implemented a lab module that allows users to seamlessly incorporate into their FPGA design. The module minimizes hardware resource utilization while enabling the acquisition of a large number of data samples from the signal during the experiments by adaptively compressing the signal prior to data transmission. The results demonstrate an average compression ratio of 2.90 across three benchmark signals, indicating efficient signal acquisition and effective debugging and analysis. This method allows users to acquire more data samples than conventional methods. The proposed lab allows students to remotely test and debug their designs, bridging the gap between theory and practice in embedded system design.
Detecting and resolving feature envy through automated machine learning and m...IJECEIAES
Efficiently identifying and resolving code smells enhances software project quality. This paper presents a novel solution, utilizing automated machine learning (AutoML) techniques, to detect code smells and apply move method refactoring. By evaluating code metrics before and after refactoring, we assessed its impact on coupling, complexity, and cohesion. Key contributions of this research include a unique dataset for code smell classification and the development of models using AutoGluon for optimal performance. Furthermore, the study identifies the top 20 influential features in classifying feature envy, a well-known code smell, stemming from excessive reliance on external classes. We also explored how move method refactoring addresses feature envy, revealing reduced coupling and complexity, and improved cohesion, ultimately enhancing code quality. In summary, this research offers an empirical, data-driven approach, integrating AutoML and move method refactoring to optimize software project quality. Insights gained shed light on the benefits of refactoring on code quality and the significance of specific features in detecting feature envy. Future research can expand to explore additional refactoring techniques and a broader range of code metrics, advancing software engineering practices and standards.
Smart monitoring technique for solar cell systems using internet of things ba...IJECEIAES
Rapidly and remotely monitoring and receiving the solar cell systems status parameters, solar irradiance, temperature, and humidity, are critical issues in enhancement their efficiency. Hence, in the present article an improved smart prototype of internet of things (IoT) technique based on embedded system through NodeMCU ESP8266 (ESP-12E) was carried out experimentally. Three different regions at Egypt; Luxor, Cairo, and El-Beheira cities were chosen to study their solar irradiance profile, temperature, and humidity by the proposed IoT system. The monitoring data of solar irradiance, temperature, and humidity were live visualized directly by Ubidots through hypertext transfer protocol (HTTP) protocol. The measured solar power radiation in Luxor, Cairo, and El-Beheira ranged between 216-1000, 245-958, and 187-692 W/m 2 respectively during the solar day. The accuracy and rapidity of obtaining monitoring results using the proposed IoT system made it a strong candidate for application in monitoring solar cell systems. On the other hand, the obtained solar power radiation results of the three considered regions strongly candidate Luxor and Cairo as suitable places to build up a solar cells system station rather than El-Beheira.
An efficient security framework for intrusion detection and prevention in int...IJECEIAES
Over the past few years, the internet of things (IoT) has advanced to connect billions of smart devices to improve quality of life. However, anomalies or malicious intrusions pose several security loopholes, leading to performance degradation and threat to data security in IoT operations. Thereby, IoT security systems must keep an eye on and restrict unwanted events from occurring in the IoT network. Recently, various technical solutions based on machine learning (ML) models have been derived towards identifying and restricting unwanted events in IoT. However, most ML-based approaches are prone to miss-classification due to inappropriate feature selection. Additionally, most ML approaches applied to intrusion detection and prevention consider supervised learning, which requires a large amount of labeled data to be trained. Consequently, such complex datasets are impossible to source in a large network like IoT. To address this problem, this proposed study introduces an efficient learning mechanism to strengthen the IoT security aspects. The proposed algorithm incorporates supervised and unsupervised approaches to improve the learning models for intrusion detection and mitigation. Compared with the related works, the experimental outcome shows that the model performs well in a benchmark dataset. It accomplishes an improved detection accuracy of approximately 99.21%.
Developing a smart system for infant incubators using the internet of things ...IJECEIAES
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Dynamic Hilbert clustering based on convex set for web services aggregation
1. International Journal of Electrical and Computer Engineering (IJECE)
Vol. 13, No. 6, December 2023, pp. 6654~6662
ISSN: 2088-8708, DOI: 10.11591/ijece.v13i6.pp6654-6662 6654
Journal homepage: http://ijece.iaescore.com
Dynamic Hilbert clustering based on convex set for web services
aggregation
Nawras A. Al-Musawi, Dhiah Al-Shammary
College of Computer Science and Information Technology, University of Al-Qadisiyah, Diwaniyah, Iraq
Article Info ABSTRACT
Article history:
Received Oct 13, 2022
Revised Mar 18, 2023
Accepted Apr 3, 2023
In recent years, web services run by big corporations and different
application-specific data centers have all been embraced by several
companies worldwide. Web services provide several benefits when
compared to other communication technologies. However, it still suffers
from congestion and bottlenecks as well as a significant delay due to the
tremendous load caused by a large number of web service requests from end
users. Clustering and then aggregating similar web services as one
compressed message can potentially achieve network traffic reduction. This
paper proposes a dynamic Hilbert clustering as a new model for clustering
web services based on convex set similarity. Mathematically, the suggested
models compute the degree of similarity between simple object access
protocol (SOAP) messages and then cluster them into groups with high
similarity. Next, each cluster is aggregated as a compact message that is
finally encoded by fixed-length or Huffman. The experiment results have
shown the suggested model performs better than the conventional clustering
techniques in terms of compression ratio. The suggested model has produced
the best results, reaching up to 15 with fixed-length and up to 20 with
Huffman
Keywords:
Aggregation
Clustering
Hilbert
Message
Web services
This is an open access article under the CC BY-SA license.
Corresponding Author:
Nawras A. Al-Musawi
College of Computer Science and Information Technology, University of Al-Qadisiyah
Diwaniyah, Iraq
Email: nawras.kadhim@qu.edu.iq
1. INTRODUCTION
Web services can be defined as web application that communicates with other systems using
standard Internet mechanisms such as hypertext transfer protocol (HTTP) and extensible markup language
(XML) in order to provide the required service to the user [1]–[3]. Web services are competitive technologies
that allow e-business and e-commerce by offering clients quick, efficient, and dependable services through
the internet [4]. Web services are a kind of simple object access (SOA)-based distributed computing
paradigm that can be accessed through HTTP. Web servers offer dynamic replies for all requests made via
the internet [5]–[7]. Web service architecture refers to the software system design for supporting
interoperable communication from machine to machine via a network [1], [8]. Web services have become
one of the most important areas of technological development in recent years [4], [9]. Web services represent
the most usable communication protocol over the net. Web services communication is built on standard
technologies such as simple object access protocol (SOAP), web service description language (WSDL), and
universal description discovery and integration (UDDI) [10], [11]. The SOAP protocol is a widely-used
communication protocol based on XML Web service [12], [13]. SOAP is a protocol for allowing different
distributed computing systems to communicate with each other [14]. Organizations are increasingly using
2. Int J Elec & Comp Eng ISSN: 2088-8708
Dynamic Hilbert clustering based on convex set for web services aggregation (Nawras A. Al-Musawi)
6655
web services due to the technological advantages of web services that provide interoperability and dynamic
scalability [12], [15].
The XML-based encoding of web messages has harmed the network’s efficiency due to the high
bandwidth that their excessive repetition of information has caused [16]. Because of the large amount of
XML data being sent across the network, consumers have suffered from bottlenecks and congestion [17].
Most of the time, Network latency is a major issue that often causes service delays for end users [18].
Particularly, SOAP messages are inherently large, necessitating greater bandwidth for web service requests
and responses [2], [19]. This fact has driven researchers to create solutions that minimize loads on networks
and increase the speed at which services may be provided. One of the newest suggested improvements is a
web-based messages aggregator, which works to combine several messages into a single message by
removing duplicate content [20], [21]. However, the aggregation’s efficacy depends on the degree of
similarity between aggregated messages. To provide high aggregation outcomes, a similarity measurement
model is necessary. This demand would be supported by effective clustering, which would as well as enhance
network-based web services to endpoints.
Technically, the proposed model has provided several major contributions in regard to the web
service performance over the network. Firstly, it would improve web-based communication over the network
by significantly reducing the required network volume. This fact would solve the network congestion and
bottleneck significantly. Secondly, efficient web messages clustering has been achieved based on Hilbert
similarity measurements. Finally, the proposed model would potentially improve web service response time
as a result of the required low processing time.
An efficient evaluation strategy is established and executed by evaluating the effectiveness of the
suggested model. This is accomplished by sending the results of its grouped message to the aggregator model
developed by [17], [22] and examining its effects on processing times and compression ratios for network
traffic reductions. Other clustering models, including k-means and principal component analysis (PCA)
coupled with k-means, are treated in the same way since they serve as a standard for the suggested clustering
method. Compared to other methods, the Hilbert clustering model has been shown to be superior due to its
ability to achieve similar outcomes while using less processing time and generating significantly less network
traffic.
The rest of this paper is structured as: section 2 explains the related work. Section 3 describes the
proposed model. Experiments and results are discussed in section 4. Finally, section 5 presents the conclusion
and future work.
2. RELATED WORK
XML message clustering is essential in web service environments and applications. Machine
learning methods have often been used for clustering web services. Many researchers have technically
presented different clustering methods for textual and XML documents. The primary focus of the proposed
clustering models has been on clustering XML documents. Similarly, another major trend in clustering
methods is focused on numerical data and hence cannot be used to text without first being converted to a
similar binary form.
Hwang and Gu [23] presented a new approach to grouping XML texts based on the repetitive
structure weight in XML texts, treating XML document is viewed as a transaction and its structures are
extracted as transactional items. The suggested method focuses on the idea of identifying the large elements
included in each XML document and then grouping them together based on their similarities. Evaluation
metrics consist of XML tag and data item paths in the XML tree. A basic principle of the suggested method
is to allocate new XML documents according to an average of the accumulated frequency of structures in the
XML tree. The suggested method is compared to both the hierarchical agglomerative clustering (HAC) and
k-means methods to determine its efficacy. The experimental results demonstrate that the suggested method
outperforms both HAC and k-means.
The extended vector space model (EVSM) was developed by Yongming et al. [24] as a novel model
for grouping XML documents according to their structure and content by calculating similarities between
them. Additionally, the hierarchical clustering method has been used in this approach. The effectiveness of
the suggested clustering approach was measured using two different criteria. Purity and entropy are two of
these measures. Their model has been experimentally tested on two datasets (the INEX IEEE corpus and the
Wikipedia collection). According to the findings, this approach would result in more efficient clustering.
A dynamic clustering approach for SOAP web messages was implemented by Al-Shammary et al.
[17] based on fractal similarity measurements. The clustered messages resultant has been formed in a
compact form for network traffic reducing. The proposed model has been examined using the compression
ratio and processing time. By analyzing the web aggregator’s resulting compression ratio (CR), the suggested
model has been compared with both k-means and PCA+k-means. The dataset has been utilized for testing
3. ISSN: 2088-8708
Int J Elec & Comp Eng, Vol. 13, No. 6, December 2023: 6654-6662
6656
and experimentation consist of 160 SOAP messages, divided into four sets of 40 messages each. These
messages were created using the WSDL for stock quotes found at [25]. The highest Av.CR values were
obtained for the following datasets, in that order: 3.92, 7.98, 16.63, and 21.70. Average processing time for
the proposed model takes around 15.6 milliseconds.
3. PROPOSED MODEL
This section explains the complete design for proposed model including Hilbert convex function,
web services aggregation and Hilbert clustering model. First, Hilbert convex set as similarity measurements
are explained with the mathematical and equations. Moreover, the proposed model includes the implemented
techniques for web service aggregation that combine web messages in a compact size based on the Hilbert
similarity grouping. Finally, the proposed model has included a new dynamic clustering technique based on
Hilbert measurements.
3.1. Hilbert convex set as similarity measurements
In this research, we have proposed Hilbert based on convex set measurements for SOAP messages
clustering. We have considered each message as convex (set) and each feature in the message as a point.
Technically, convex set measurements are applied to calculate the similarity between two messages.
Equation (1) illustrates the Hilbert convex set measurements, including their parameters:
𝑆𝑖𝑚 (𝑥, 𝑦) =
∑ (𝑋𝑖∗𝑌𝑖)– 𝑀𝑎𝑥 (𝑥)
𝑛
𝑖=1
‖𝑥‖∗ ‖𝑦‖
(1)
‖𝑥‖ = √𝑥1
2
+ 𝑥2
2
+ 𝑥3
2
+ ⋯ (2)
‖𝑦‖ = √𝑦1
2
+ 𝑦2
2
+ 𝑦3
2
+ ⋯ (3)
where, x and y are vectors (x and y are represented by SOAP messages), n is number of attributes in vector,
and Max(x) is maximum value in vector x.
3.2. Web service aggregation
In this study, an aggregation model based on compression [17], [22] is used to examine the
performance of the suggested approach. The paradigm of aggregation consists of three phases leading to a
compact aggregated message. Initially, XML messages are transformed into a web matrix (in matrix form),
and then they are represented as an XML tree. XML trees are then transformed into vectors using either
depth-first or breadth-first tree traversal. These text expressions are compressed using either the fixed-length
or Huffman lossless compression methods. The suggested model has been formed into two primary
approaches: one-bit and two-bit aggregators. Both aggregators provide two versions of the fixed-length and
Huffman encoding techniques.
3.3. Dynamic Hilbert clustering model
A novel Hilbert clustering technique is proposed to provide dynamic clustering for web services.
Hilbert space and distance measurements are introduced as new mathematical computations for the similarity
between XML messages. Hilbert is suggested as a strategy for unsupervised clustering, which groups XML
messages in a dynamic manner. The presented approach intends to build clusters with a high similarity
degree by grouping messages together dynamically without requiring a fixed number of clusters. The
proposed model first converts Web messages into numeric form developed by Al-Shammary et al. [17] and
Hwang and Gu [23]. Next, Hilbert convex set measurements are achieved on the numeric representations of
XML messages. Technically, Hilbert similarity measurements are applied in order to cluster XML messages
based on the maximum similarity values. The final Hilbert clusters would be the input to the We aggregators
to aggregate each cluster’s messages together. Figure 1 explains the main steps of the proposed Hilbert
clustering model.
Practically, dynamic Hilbert clustering begins with constructing an XML tree that maintains a single
occurrence in the tree while eliminating duplicate ending tags (closing tags), then employing a term
frequency-inverse document frequency (TF-IDF) weighting technique to calculate elements’ frequency for
each message. Then the outcomes of this method will be recorded in a vectors matrix of two dimensions.
Next, Hilbert convex measurements have been applied to compute the similarity degree between messages.
Each (current) message’s Hilbert similarity measurements are computed with all messages and compared,
4. Int J Elec & Comp Eng ISSN: 2088-8708
Dynamic Hilbert clustering based on convex set for web services aggregation (Nawras A. Al-Musawi)
6657
and the message is then assigned to the cluster with the highest similarity value. Eventually, the resulting
clusters are constructed in the string form and input into an aggregator tool. This tool combines the contents
of each cluster of messages that are similar into a single compressed message. Figure 2 shows a detailed
explanation of all steps taken by the dynamic clustering model. Algorithm 1 illustrate this process.
Figure 1. Main steps of Hilbert clustering
Figure 2. Dynamic Hilbert clustering model
5. ISSN: 2088-8708
Int J Elec & Comp Eng, Vol. 13, No. 6, December 2023: 6654-6662
6658
Algorithm 1. Dynamic Hilbert clustering (messages distribution)
//Definitions
Sn //Number of message in dataset
Cn //Number of clusters
Vs //Vector items
Vflag (Sn) //Array of flag to determine the allocated centers
For i=1 to Sn //compute sum weight and find norm for all messages
Norm (i)=√∑ 𝑋𝑓
2
𝑁
𝑓=1
End for
For i=1 to Vs //All vector items
//find Maximum value (Max)
End for
For i=1 to Sn //Compute Hilbert similarity
If Vflag (i)=false then
For j=1 to Sn//All messages
If (i< >j) then
Dot=∑ [𝑊𝑗(𝑟) × 𝑊𝑖(𝑟)
𝑁
𝑟=1 ]
HS (i)=
𝐷𝑜𝑡−𝑀𝑎𝑥(𝑖)
𝑁𝑜𝑟𝑚(𝑖)×𝑁𝑜𝑟𝑚(𝑗)
//Find maximum similarity (closest message)
End if
End for
//Add message to the cluster
//Exclude message
End if
End for
For i=1 to Cn
//generate string form for all allocation vectors (clusters)
End for
4. EXPERIMENTS AND RESULTS
In order to evaluate the performance of the proposed Hilbert clustering model, a wide range of XML
message sizes has been considered in the experimental analysis. The dataset was formed using the WSDL
at [25]. It contains 160 messages divided into four groups based on their size. Which categories: small,
medium, large, and very large, with sizes ranging from 140 to 5,500 bytes. Each group has 40 messages [17].
We have used the compression-based aggregation model [22] to investigate the proposed model’s efficiency
compared to other standard clustering methods. Vector space model [26] has been applied to the same dataset
and compared with the proposed model. The main evaluation metrics include compression ratio, clustering
time and compressed size file that are computed by aggregator tool on the resultant clusters. The highest CR
achieved by these methods means this is the best clustering. Furthermore, other comparisons are applied with
k-means and PCA+k-means from previous studies [17], [27].
In order to achieve potentially large compression ratios on the clustered XML messages, all
strategies demonstrated substantial results. Experimentally, the structure of clusters for each group is
explained in Table 1. The clusters that formed as a result of the small group distribute different numbers of
XML messages (10, 20, 30, and 40) into variety clusters (3, 8, 10, 13), illustrating the dynamic nature of the
Hilbert model since the size of the cluster is not predetermined. In the medium group, the number of clusters
is 3, 6, 9, and 11, including 10, 20, 30, and 40 messages, respectively. Then again, the large group with 10,
20, 30, and 40 messages distributed into 3, 6, 6, and 7 clusters and finally, the very large group was divided
into 3, 5, 7, and 8 clusters for 10, 20, 30, and 40 message respectively. Clearly, the cluster number decreases
with the message size increase. This is because larger XML messages have more redundancy, which in turn
causes a fewer number of clusters to be allocated to messages than is the case of smaller files. Moreover,
most clusters are about equal size. This shows that a dynamic model can efficiently distribute web messages
of such size, which may be more appropriate than several others.
Moreover, the average CR results achieved by applying the dynamic model to the dataset are
3.2056334, 7.2671758, 13.8358308, and 15.3180299 for small, medium, large, and very large groups,
respectively, with 40 messages in the fixed-length method. On the other hand, when implementing the
proposed model with the Huffman technique, the average CR results are 3.0780064, 7.8991900, 17.6439850,
and 20.4135664 for small, medium, large, and very large groups, respectively, with 40 messages. Evidently,
the dynamic model performance with the Huffman technique has shown better CR results than the fixed-
length method. The average values obtained for CR are stated in Table 2. Table 3 presents the resultant
average CR for the proposed model compared with k-means, PCA combined with k-means, and vector space
clustering techniques for all groups with 40 messages and different cluster sizes. It has shown the
performance of the dynamic Hilbert clustering model as better than other models (k-means, k-means+PCA)
6. Int J Elec & Comp Eng ISSN: 2088-8708
Dynamic Hilbert clustering based on convex set for web services aggregation (Nawras A. Al-Musawi)
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in medium, large and very large groups, as well as it has outperformed the vector space model in large and
very large groups of messages.
Table 1. Clusters number results of dynamic Hilbert model for small, medium, large, and very large groups
with 10, 20, 30, and 40 message
Message group Messages number Clusters number Cluster size
Small 10 3 4, 2, 4
Medium 3 3, 5, 2
Large 3 3, 5, 2
Very large 3 3, 4, 3
Small 20 8 2, 2, 3, 3, 3, 2, 3, 2
Medium 6 2, 10, 2, 2, 2, 2
Large 6 4, 4, 4, 2, 3, 3
Very large 5 5, 5, 2, 5, 3
Small 30 10 4, 4, 4, 3, 2, 2, 2, 3, 4, 2
Medium 9 2, 4, 9, 2, 2, 2, 2, 5, 2
Large 6 6, 11, 5, 2, 3, 3
Very large 7 7, 3, 7, 4, 5, 5, 2
Small 40 13 4, 3, 2, 4, 5, 2, 2, 5, 2, 4, 2, 2, 3
Medium 11 2, 5, 2, 13, 2, 2, 3, 2, 2, 2, 5
Large 7 8, 14, 2, 6, 2, 4, 4
Very large 8 12, 6, 5, 2, 4, 4, 2, 5
Table 2. Average compression ratio results of dynamic Hilbert model for small, medium, large, and
very large groups with 10, 20, 30, and 40 message
Technique Number of messages Average compression ratio
Small Medium Large Very large
Fixed-length 10 3.2697077 5.7443354 12.4924011 14.9570576
Huffman 3.1260245 5.9219548 15.3183671 19.2842577
Fixed-length 20 2.9457311 6.7048004 12.5591163 15.1736808
Huffman 2.8026315 7.2287170 15.4996723 19.7894517
Fixed-length 30 3.1320684 6.5375936 13.5885417 15.1863710
Huffman 3.0049905 6.9910348 17.3358167 20.0347384
Fixed-length 40 3.2056334 7.2671758 13.8358308 15.3180299
Huffman 3.0780064 7.8991900 17.6439850 20.4135664
Table 3. Overall average compression ratio of k-means, PCA+k-means, Hilbert, vector space for small,
medium, large and very large groups with 40 messages in both fixed-length and variable-length (Huffman)
compression techniques
K-means K-means + PCA Hilbert (dynamic) Vector space
40 Small messages
Fixed-length average cr. 3.920295 3.850353 3.205633 3.626756
Huffman average cr. 3.820822 3.7136433 3.078006 3.542261
40 Medium messages
Fixed-length average cr. 6.766314 6.797503 7.267175 7.340936
Huffman average cr. 7.715699 7.843987 7.899190 7.971288
40 Large messages
Fixed-length average cr. 12.943645 12.815021 13.835830 13.208350
Huffman average cr. 16.020012 16.279294 17.643985 16.602675
40 Very large messages
Fixed-length average cr. 15.109293 15.127478 15.318029 15.229273
Huffman average cr. 20.163554 20.253857 20.413566 20.169220
Several illustrative figures have been computed in order to show the outcome in a clear manner.
Figure 3 shows the detailed results of average clustering time for small, medium, large and very large groups
with (10, 20, 30, and 40) message numbers in both fixed-length as shown in Figure 3(a) and Huffman as
shown in Figure 3(b) encoding. Evidently, the clustering time has shown the best values with a small size of
messages. This indicates that the needed processing time increase as the number of messages increases.
Figure 4 depicts the ability to minimize the overall size of the aggregated messages with various original
sizes for small as shown in Figure 4(a), medium in Figure 4(b), large in Figure 4(c), and very large in
Figure 4(d). Moreover, the proposed model has achieved better results with the Huffman technique than with
the fixed-length technique.
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(a) (b)
Figure 3. Average clustering time of dynamic Hilbert clustering model for all groups of messages in
(a) fixed-length and (b) Huffman techniques
(a) (b)
(c) (d)
Figure 4. Compressed size for (a) small, (b) medium, (c) large, and (d) very large in both fixed-length and
Huffman techniques
0
5000
10000
10 20 30 40
CLUSTERING
TIME
(MS)
NUMBER OF MESSAGES
Fixed-length
small medium large very large
0
5000
10000
10 20 30 40
CLUSTERING
TIME
(MS)
NUMBER OF MESSAGES
Huffman
small medium large very large
0
10000
20000
10 20 30 40
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(byte)
Number of messages
Compressed size
Fixed-Length Huffman Orginal size
0
100000
200000
300000
400000
500000
10 20 30 40
Size
(byte)
Number of messages
Compressed size
Fixed-Length Huffman Original size
0
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10 20 30 40
Size
(byte)
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Compressed size
Fixed-Length Huffman Original size
0
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(byte)
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Dynamic Hilbert clustering based on convex set for web services aggregation (Nawras A. Al-Musawi)
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5. CONCLUSION
In conclusion, this paper has introduced a new Hilbert clustering model based on a convex set. The
main technique is computing the similarity values between web service messages and clustering them. The
experimental results have shown the proposed model’s effectiveness in dramatically enabling the aggregation
approach to reduce network traffic compared to other traditional methods. The proposed model can achieve a
high compression ratio that reaches up to 20 with the Huffman technique. Moreover, it has provided a
considerable reduction in processing time. In the future, we will apply the proposed model to high
dimensional dataset and use Hilbert similarity measurements for web services classification.
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BIOGRAPHIES OF AUTHORS
Nawras A. Al-Musawi received her M.Sc. degree in computer science from the
college of computer science and information technology at the University of Al-Qadisiyah-
Iraq in 2022. She has obtained a Bachelor degree in computer science from the College of
Science at the University of Al-Qadisiyah-Iraq in 2009. She has worked in teaching of
computer science courses for high school students for several years. Nawras has an interest in
research on web services, data compression, clustering techniques and encoding methods. She
can be contacted at email: nawras.kadhim@qu.edu.iq.
Dhiah Al-Shammary has received his Ph.D. in Computer Science in 2014 from
RMIT University, Melbourne, Australia. Dhiah is awarded as the best Ph.D. student and top
publication during his Ph.D. period. He has several years experience in both education and
industry. His main industrial experience came from Silicon Valley based companies working
on security projects including non-traditional and quantum scale encryption. Dhiah has
worked at several universities in both Australia and Iraq like RMIT University and University
of Al-Qadisiyah. His research interests include performance modelling, web services,
compression and encoding techniques, and distributed systems. Dhiah has several publications
in the areas of improving the performance of web services and encoding techniques. He can be
contacted at email: d.alshammary@qu.edu.iq.