The document describes a study that used Colored Petri Nets (CPN) to model and simulate task migration in pervasive cloud computing environments. The study made the following contributions:
1) It expanded the semantics of CPN to include context information, creating a new CPN model called CCPN.
2) Using CCPN, it constructed two task migration models - one that considered context and one that did not - to simulate task migration in a pervasive cloud based on the OSGi framework.
3) It simulated the two models in CPN Tools and evaluated them based on metrics like task migration accessibility, integrity of the migration process, and system reliability and stability after migration. It also
Web Service QoS Prediction Based on Adaptive Dynamic Programming Using Fuzzy ...redpel dot com
Web Service QoS Prediction Based on Adaptive Dynamic Programming Using Fuzzy Neural Networks for Cloud Services
for more ieee paper / full abstract / implementation , just visit www.redpel.com
k fault tolerance Mobile Adhoc Network under Cost Constraintsugandhasinghhooda
A network topology is a K-FT topology if it can endure K number of link failures, however to find a reliable hardware topology for a set of nodes keeping the total cost of the links within a predefined budget, is a challenging task, especially when the topology is subjective to constraints that the topological network can tolerate K link failures keeping total cost of network within budget. This problem has been addressed in this paper where in a novel algorithm is proposed that uses N X N matrix to represent the cost between the participating nodes, and uses K-FT topology to tackle the fault tolerant problem of Mobile Adhoc Networks. Intention is to achieve optimal resource utilization and fairness among competing end to end flows. A network topology is said to be K-FT if and only if every pair of node is reachable from all other nodes for K link failures. The algorithm has been tested for wide range of node sets and the result obtained there of suggest that the proposed algorithm finds better solutions in comparison to Genetic Algorithm.
Performance Analysis of Bfsk Multi-Hop Communication Systems Over K-μ Fading ...ijwmn
Multi-hop communication systems gained popularity in wireless communications; they can be used to
extend the coverage of the network and reduce the transmitted power. The transmission of data from the
source node to the destination node in multi-hop communications undergoes through intermediate relay
nodes. In this paper, we study the performance of multi-hop communication systems, in terms of average bit
error rate (BER) with Binary frequency shift keying assuming the κ-µ fading channel model. Due to the
difficulty in finding the probability density function (PDF) of the end-to-end signal to noise ratio (SNR) and
hence for the performance metrics, we use Gaussian Mixture (GM) approximation technique to
approximate the PDF of the end to end SNR assuming the κ-µ fading models as weighted sums of Gaussian
distributions. Numerical results are provided for the BER of binary frequency shift keying (BFSK) of
amplify and forward (AF) multi-hop communication systems assuming different values for the fading
parameters (, ) and for different number of hops. Numerical results are validated by comparing them
with simulation results.
Hybrid multi objectives genetic algorithms and immigrants scheme for dynamic ...khalil IBRAHIM
the main concept of intelligent optimization techniques, artificial neural networks, and new genetic algorithms to solve the multi-objective multicast routing problems with shortest path (SP) problem that used in the addresses networks and improve all processes addressing in the wireless communications based on multi-objective optimization. The most important characteristics in mobile wireless networks is the topology dynamics and the network topology changes over time, the routing problem (SPRP) in mobile ad hoc networks (MANETs) turns out to be a dynamic optimization problem[13], the hybrid immigrants multiple-objective genetic algorithm (HIMOGAs) in the real- world are dynamic in nature, that has objective functions, constraints, and parameters, the dynamic optimization problems (DOPs) are a big challenges to evolutionary multi-objective, since any environmental change may affect the objective vector, constraints, and parameters, HIMOGA for the optimization goal is to track the moving of parameters and get a sequence of approximations solutions over time. The quantity of services (QoS) is supporting guarantee for all data traffic and getting the maximizing utilization for network, the QoS based on multicast routing offers significant challenges, and increases to use an efficient multicast routing protocol that will be able to check multicast routing and satisfying QoS constraints, The author propose to use HIMOGAs and SP algorithm to solve multicast problem that produces new generation wireless networks with immigrants schema to get high-quality solutions after each change and satisfying all objectives.
Enhancement of Single Moving Average Time Series Model Using Rough k-Means fo...IJERA Editor
In the last decade, real–time audio and video services have gained much popularity, and now occupying a large portion of the total network traffic in the Internet. As the real-time services are becoming mainstream the demand for Quality of Service (QoS) is greater than ever before. It is necessary to use the network resources to the fullest, to satisfy the increasing demand for QoS. To solve this issue, we need to apply a prediction model for network traffic, on the basis of network management such as congestion control and bandwidth location. In this paper, we propose an integrated model that combines Rough K-Means (RKM) clustering with Single Moving Average (SMA) time series model to improve prediction loading packets of network traffic. The single moving average time series prediction model is used to predict loading of packets volume in real network traffic. Further, clustering granules obtained by using rough k-means is used to analyze the network data of each year separately. The proposed model is an integration of the prediction results that were obtained from conventional single moving average prediction model with centriods of clusters that obtained from rough k-means clustering. The model is evaluated using on line network traffic data that has been collected from WIDE backbone Network MSE, RMSE and MAPE metrics are used to examine the results of the integrated model. The experimental results show that the integrated model can be an effective way to improve prediction accuracy achieved with the help of rough k-means clustering. A Comparative result between conventional prediction model and our integrated model is presented.
A Baye's Theorem Based Node Selection for Load Balancing in Cloud Environmentneirew J
Cloud computing is a popular computing model as it renders service to large number of users request on
the fly and has lead to the proliferation of large number of cloud users. This has lead to the overloaded
nodes in the cloud environment along with the problem of load imbalance among the cloud servers and
thereby impacts the performance. Hence, in this paper a heuristic Baye's theorem approach is considered
along with clustering to identify the optimal node for load balancing. Experiments using the proposed
approach are carried out on cloudsim simulator and are compared with the existing approach. Results
demonstrates that task deployment performed using this approach has improved performance in terms of
utilization and throughput when compared to the existing approaches.
Web Service QoS Prediction Based on Adaptive Dynamic Programming Using Fuzzy ...redpel dot com
Web Service QoS Prediction Based on Adaptive Dynamic Programming Using Fuzzy Neural Networks for Cloud Services
for more ieee paper / full abstract / implementation , just visit www.redpel.com
k fault tolerance Mobile Adhoc Network under Cost Constraintsugandhasinghhooda
A network topology is a K-FT topology if it can endure K number of link failures, however to find a reliable hardware topology for a set of nodes keeping the total cost of the links within a predefined budget, is a challenging task, especially when the topology is subjective to constraints that the topological network can tolerate K link failures keeping total cost of network within budget. This problem has been addressed in this paper where in a novel algorithm is proposed that uses N X N matrix to represent the cost between the participating nodes, and uses K-FT topology to tackle the fault tolerant problem of Mobile Adhoc Networks. Intention is to achieve optimal resource utilization and fairness among competing end to end flows. A network topology is said to be K-FT if and only if every pair of node is reachable from all other nodes for K link failures. The algorithm has been tested for wide range of node sets and the result obtained there of suggest that the proposed algorithm finds better solutions in comparison to Genetic Algorithm.
Performance Analysis of Bfsk Multi-Hop Communication Systems Over K-μ Fading ...ijwmn
Multi-hop communication systems gained popularity in wireless communications; they can be used to
extend the coverage of the network and reduce the transmitted power. The transmission of data from the
source node to the destination node in multi-hop communications undergoes through intermediate relay
nodes. In this paper, we study the performance of multi-hop communication systems, in terms of average bit
error rate (BER) with Binary frequency shift keying assuming the κ-µ fading channel model. Due to the
difficulty in finding the probability density function (PDF) of the end-to-end signal to noise ratio (SNR) and
hence for the performance metrics, we use Gaussian Mixture (GM) approximation technique to
approximate the PDF of the end to end SNR assuming the κ-µ fading models as weighted sums of Gaussian
distributions. Numerical results are provided for the BER of binary frequency shift keying (BFSK) of
amplify and forward (AF) multi-hop communication systems assuming different values for the fading
parameters (, ) and for different number of hops. Numerical results are validated by comparing them
with simulation results.
Hybrid multi objectives genetic algorithms and immigrants scheme for dynamic ...khalil IBRAHIM
the main concept of intelligent optimization techniques, artificial neural networks, and new genetic algorithms to solve the multi-objective multicast routing problems with shortest path (SP) problem that used in the addresses networks and improve all processes addressing in the wireless communications based on multi-objective optimization. The most important characteristics in mobile wireless networks is the topology dynamics and the network topology changes over time, the routing problem (SPRP) in mobile ad hoc networks (MANETs) turns out to be a dynamic optimization problem[13], the hybrid immigrants multiple-objective genetic algorithm (HIMOGAs) in the real- world are dynamic in nature, that has objective functions, constraints, and parameters, the dynamic optimization problems (DOPs) are a big challenges to evolutionary multi-objective, since any environmental change may affect the objective vector, constraints, and parameters, HIMOGA for the optimization goal is to track the moving of parameters and get a sequence of approximations solutions over time. The quantity of services (QoS) is supporting guarantee for all data traffic and getting the maximizing utilization for network, the QoS based on multicast routing offers significant challenges, and increases to use an efficient multicast routing protocol that will be able to check multicast routing and satisfying QoS constraints, The author propose to use HIMOGAs and SP algorithm to solve multicast problem that produces new generation wireless networks with immigrants schema to get high-quality solutions after each change and satisfying all objectives.
Enhancement of Single Moving Average Time Series Model Using Rough k-Means fo...IJERA Editor
In the last decade, real–time audio and video services have gained much popularity, and now occupying a large portion of the total network traffic in the Internet. As the real-time services are becoming mainstream the demand for Quality of Service (QoS) is greater than ever before. It is necessary to use the network resources to the fullest, to satisfy the increasing demand for QoS. To solve this issue, we need to apply a prediction model for network traffic, on the basis of network management such as congestion control and bandwidth location. In this paper, we propose an integrated model that combines Rough K-Means (RKM) clustering with Single Moving Average (SMA) time series model to improve prediction loading packets of network traffic. The single moving average time series prediction model is used to predict loading of packets volume in real network traffic. Further, clustering granules obtained by using rough k-means is used to analyze the network data of each year separately. The proposed model is an integration of the prediction results that were obtained from conventional single moving average prediction model with centriods of clusters that obtained from rough k-means clustering. The model is evaluated using on line network traffic data that has been collected from WIDE backbone Network MSE, RMSE and MAPE metrics are used to examine the results of the integrated model. The experimental results show that the integrated model can be an effective way to improve prediction accuracy achieved with the help of rough k-means clustering. A Comparative result between conventional prediction model and our integrated model is presented.
A Baye's Theorem Based Node Selection for Load Balancing in Cloud Environmentneirew J
Cloud computing is a popular computing model as it renders service to large number of users request on
the fly and has lead to the proliferation of large number of cloud users. This has lead to the overloaded
nodes in the cloud environment along with the problem of load imbalance among the cloud servers and
thereby impacts the performance. Hence, in this paper a heuristic Baye's theorem approach is considered
along with clustering to identify the optimal node for load balancing. Experiments using the proposed
approach are carried out on cloudsim simulator and are compared with the existing approach. Results
demonstrates that task deployment performed using this approach has improved performance in terms of
utilization and throughput when compared to the existing approaches.
A BAYE'S THEOREM BASED NODE SELECTION FOR LOAD BALANCING IN CLOUD ENVIRONMENThiij
Cloud computing is a popular computing model as it renders service to large number of users request on
the fly and has lead to the proliferation of large number of cloud users. This has lead to the overloaded
nodes in the cloud environment along with the problem of load imbalance among the cloud servers and
thereby impacts the performance. Hence, in this paper a heuristic Baye's theorem approach is considered
along with clustering to identify the optimal node for load balancing. Experiments using the proposed
approach are carried out on cloudsim simulator and are compared with the existing approach. Results
demonstrates that task deployment performed using this approach has improved performance in terms of
utilization and throughput when compared to the existing approaches
PAGE: A Partition Aware Engine for Parallel Graph Computation1crore projects
IEEE PROJECTS 2015
1 crore projects is a leading Guide for ieee Projects and real time projects Works Provider.
It has been provided Lot of Guidance for Thousands of Students & made them more beneficial in all Technology Training.
Dot Net
DOTNET 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
7. IEEE based on parallel and distributed systems
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
7. IEEE based on parallel and distributed systems
ECE IEEE Projects 2015
1. Matlab project
2. Ns2 project
3. Embedded project
4. Robotics project
Eligibility
Final Year students of
1. BSc (C.S)
2. BCA/B.E(C.S)
3. B.Tech IT
4. BE (C.S)
5. MSc (C.S)
6. MSc (IT)
7. MCA
8. MS (IT)
9. ME(ALL)
10. BE(ECE)(EEE)(E&I)
TECHNOLOGY USED AND FOR TRAINING IN
1. DOT NET
2. C sharp
3. ASP
4. VB
5. SQL SERVER
6. JAVA
7. J2EE
8. STRINGS
9. ORACLE
10. VB dotNET
11. EMBEDDED
12. MAT LAB
13. LAB VIEW
14. Multi Sim
CONTACT US
1 CRORE PROJECTS
Door No: 214/215,2nd Floor,
No. 172, Raahat Plaza, (Shopping Mall) ,Arcot Road, Vadapalani, Chennai,
Tamin Nadu, INDIA - 600 026
Email id: 1croreprojects@gmail.com
website:1croreprojects.com
Phone : +91 97518 00789 / +91 72999 51536
Achieving Optimum Value of k in a K-fold Multicast Network with Buffer using ...cscpconf
Multicast network is widely used for effective communication, transmission and performance
optimizations of a network. In this paper, a new model has been developed to determine a
suitable value of the fold k of a k-fold multicast network under different traffic loads under
Poisson traffic with finite queue at each node. We have derived stationary distribution for the
network states and then derived expressions for the network throughput and the blocking
probability of the network. It has been found in this research work that the network throughput
increases very fast as we increase the fold number. However, at a certain value of the fold, the
blocking probability ceases to increase and it remains constant. We have also observed that as
the offered traffic is increased, the throughput also increases. Moreover, the system parameter k
is increased, the blocking probability decreases. However, after an optimum value of k, the
blocking probability remains constant for a particular value of the offered traffic. In fact, in this
paper, by evaluating the performance of a k-fold multicast network, our developed model improves the performance of a multicast network.
Enforcing end to-end proportional fairness with bounded buffer overflow proba...ijwmn
In this paper, we present a distributed flow-based
access scheme for slotted-time protocols, that prov
ides
proportional fairness in ad-hoc wireless networks u
nder constraints on the buffer overflow probabiliti
es at
each node. The proposed scheme requires local infor
mation exchange at the link-layer and end-to-end
information exchange at the transport-layer, and is
cast as a nonlinear program. A medium access contr
ol
protocol is said to be proportionally fair with res
pect to individual end-to-end flows in a network, i
f the
product of the end-to-end flow rates is maximized.
A key contribution of this work lies in the constru
ction of
a distributed dual approach that comes with low com
putational overhead. We discuss the convergence
properties of the proposed scheme and present simul
ation results to support our conclusions.
Optimal Configuration of Network Coding in Ad Hoc Networks1crore projects
IEEE PROJECTS 2015
1 crore projects is a leading Guide for ieee Projects and real time projects Works Provider.
It has been provided Lot of Guidance for Thousands of Students & made them more beneficial in all Technology Training.
Dot Net
DOTNET 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
7. IEEE based on parallel and distributed systems
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
7. IEEE based on parallel and distributed systems
ECE IEEE Projects 2015
1. Matlab project
2. Ns2 project
3. Embedded project
4. Robotics project
Eligibility
Final Year students of
1. BSc (C.S)
2. BCA/B.E(C.S)
3. B.Tech IT
4. BE (C.S)
5. MSc (C.S)
6. MSc (IT)
7. MCA
8. MS (IT)
9. ME(ALL)
10. BE(ECE)(EEE)(E&I)
TECHNOLOGY USED AND FOR TRAINING IN
1. DOT NET
2. C sharp
3. ASP
4. VB
5. SQL SERVER
6. JAVA
7. J2EE
8. STRINGS
9. ORACLE
10. VB dotNET
11. EMBEDDED
12. MAT LAB
13. LAB VIEW
14. Multi Sim
CONTACT US
1 CRORE PROJECTS
Door No: 214/215,2nd Floor,
No. 172, Raahat Plaza, (Shopping Mall) ,Arcot Road, Vadapalani, Chennai,
Tamin Nadu, INDIA - 600 026
Email id: 1croreprojects@gmail.com
website:1croreprojects.com
Phone : +91 97518 00789 / +91 72999 51536
MULTIUSER BER ANALYSIS OF CS-QCSK MODULATION SCHEME IN A CELLULAR SYSTEM ijwmn
In recent years, chaotic communication is a hot research topic and it suits better for the emerging wireless networks because of its excellent features. Different chaos based modulation schemes have evolved, of which the CS-DCSK modulation technique provides better BER performance and bandwidth
efficiency, due to its code domain approach. The QCSK modulation technique provides double benefit: higher data rate with similar BER performance and same bandwidth occupation as DCSK. By combining the advantage of code shifted differential chaos shift keying (CS-DCSK) and Quadrature chaos shift keying (QCSK) scheme, a novel modulation scheme called code shifted Quadrature chaos shift keying (CS-QCSK) is proposed and its suitability in a multiuser scenario is tested in this paper. The analytical expressions for the bit-error rate for Multi-user CS-QCSK scheme (MU-CS-QCSK) under Rayleigh
multipath fading channel is derived. The simulation result shows that, in multiuser scenario the proposed method outperforms classical chaotic modulation schemes in terms of bit error rate (BER).
Fuzzy Optimized Metric for Adaptive Network RoutingCSCJournals
Network routing algorithms used today calculate least cost (shortest) paths between nodes. The cost of a path is the sum of the cost of all links on that path. The use of a single metric for adaptive routing is insufficient to reflect the actual state of the link. In general, there is a limitation on the accuracy of the link state information obtained by the routing protocol. Hence it becomes useful if two or more metrics can be associated to produce a single metric that can describe the state of the link more accurately. In this paper, a fuzzy inference rule base is implemented to generate the fuzzy cost of each candidate path to be used in routing the incoming calls. This fuzzy cost is based on the crisp values of the different metrics; a fuzzy membership function is defined. The parameters of these membership functions reflect dynamically the requirement of the incoming traffic service as well as the current state of the links in the path. And this paper investigates how three metrics, the mean link bandwidth, queue utilization and the mean link delay, can be related using a simple fuzzy logic algorithm to produce a optimized cost of the link for a certain interval that is more „precise‟ than either of the single metric, to solve routing problem .
Performance Analysis for Parallel MRA in Heterogeneous Wireless NetworksEditor IJCATR
This paper analysis a different methods to find optimal path for services and power allocation to heterogeneous wireless network. Under heterogeneous wireless networks, a user can send data through a single or multi RATs (Radio Access Technology) simultaneously. The objective of this paper is to choose the optimal path for the services and power allocation to that bandwidth (BW) distributed joint allocation algorithm using Newton and modified Newton are adopted and the total system capacity compared. The analysis is done in Matlab and simulation results are compared. The numerical result shows that compare to Newton method, modified Newton method maximize the total system capacity.
PERFORMANCE FACTORS OF CLOUD COMPUTING DATA CENTERS USING [(M/G/1) : (∞/GDMOD...ijgca
The ever-increasing status of the cloud computing hypothesis and the budding concept of federated cloud computing have enthused research efforts towards intellectual cloud service selection aimed at developing techniques for enabling the cloud users to gain maximum benefit from cloud computing by selecting services which provide optimal performance at lowest possible cost. Cloud computing is a novel paradigm for the provision of computing infrastructure, which aims to shift the location of the computing infrastructure to the network in order to reduce the maintenance costs of hardware and software resources. Cloud computing systems vitally provide access to large pools of resources. Resources provided by cloud computing systems hide a great deal of services from the user through virtualization. In this paper, the cloud data center is modelled as queuing system with a single task arrivals and a task request buffer of infinite capacity.
Web Service QoS Prediction Approach in Mobile Internet Environmentsjins0618
Existing many Web service QoS prediction
approaches are very accurate in Internet environments,
however they cannot provide accurate prediction values in
Mobile Internet environments since QoS values of Web
services have great volatility. In this paper, we propose an
accurate Web service QoS prediction approach by weakening
the volatility of QoS data from Web services in Mobile Internet
environments. This approach contains three process, i.e., QoS
preprocessing, user similarity computing, and QoS predicting.
We have implemented our proposed approach with experiment
based on real world and synthetic datasets. The results show
that our approach outperforms other approaches in Mobile
Internet environments.
Device Discovery Schemes for Energy-Efficient Cluster Head Rotation in D2DTELKOMNIKA JOURNAL
In this paper, novel device discovery approaches for the cluster head rotation, which is a state-ofthe-
art method for the Device-to-Device communication, are proposed. The device discovery is the
process to detect and to include new devices in the Device-to-Device communication. The proposed
device discovery is aimed to attain energy efficiency for the communication devices. We propose two
schemes for the device discovery: eNB-assisted and independent device discovery. Compared to previous
work, the proposed device discovery is utilizing the cluster head rotation method, to achieve better energy
efficiency. In this work, several simulations were performed and discussed for both schemes. In the first
simulation, the device energy consumption is examined. After that, the number of devices that get rejected
is studied. The device discovery processes in multi cluster head scenario, which is cluster head rotation,
are examined in this paper. The result of the simulation shows that eNB-assisted device discovery can
provide better energy efficiency. Also, the number of rejected devices of the eNB-assisted device
discovery is slightly lower than independent device discovery.
AN EFFICIENT ALGORITHM FOR THE BURSTING OF SERVICE-BASED APPLICATIONS IN HYB...Nexgen Technology
bulk ieee projects in pondicherry,ieee projects in pondicherry,final year ieee projects in pondicherry
Nexgen Technology Address:
Nexgen Technology
No :66,4th cross,Venkata nagar,
Near SBI ATM,
Puducherry.
Email Id: praveen@nexgenproject.com.
www.nexgenproject.com
Mobile: 9751442511,9791938249
Telephone: 0413-2211159.
NEXGEN TECHNOLOGY as an efficient Software Training Center located at Pondicherry with IT Training on IEEE Projects in Android,IEEE IT B.Tech Student Projects, Android Projects Training with Placements Pondicherry, IEEE projects in pondicherry, final IEEE Projects in Pondicherry , MCA, BTech, BCA Projects in Pondicherry, Bulk IEEE PROJECTS IN Pondicherry.So far we have reached almost all engineering colleges located in Pondicherry and around 90km
Time Efficient VM Allocation using KD-Tree Approach in Cloud Server Environmentrahulmonikasharma
Cloud computing is an incipient and quickly evolving model, with new expenses and capabilities being proclaimed frequently. The increases of user on cloud with the expansion of variety of services, with that the complete allocation of resource with the minimum latent time for Virtual machine is necessary. To allocate this virtual cloud computing resources to the cloud user is a key technical issue because user demand is dynamic in nature that required dynamic allocation of resource too. To improve the allocation there must be a correct balanced algorithmic scheduling for Resource Allocation Technique. The aim of this work is to allocate resource to scientific experiment request coming from multiple users, wherever customized Virtual machines (VM) are aloft in applicable host out there in cloud. Therefore, properly programmed scheduling cloud is extremely vital and it’s significant to develop efficient scheduling methods for appropriately allocation of VMs into physical resource. The planned formulas minimize the time interval quality so as of O (Log n) by adopting KD-Tree.
Further Analysis Of A Framework To Analyze Network Performance Based On Infor...CSCJournals
Abstract In [1], Geng and Li presented a framework to analyze network performance based on information quality. In that paper, the authors based their framework on the flow of information from a Base Station (BS) to clients. The theory they established can, and needs, to be extended to accommodate for the flow of information from the clients to the BS. In this work, we use that framework and study the case of client to BS data transmission. Our work closely parallels the work of Geng and Li, we use the same notation and liberally reference their work. Keywords: information theory, information quality, network protocols, network performance
Style transfer aims to combine the content of one image with the artistic style of another. It was discovered that lower levels of convolutional networks captured style information, while higher levels captures content information. The original style transfer formulation used a weighted combination of VGG-16 layer activations to achieve this goal. Later, this was accomplished in real-time using a feed-forward network to learn the optimal combination of style and content features from the respective images. The first aim of our project was to introduce a framework for capturing the style from several images at once. We propose a method that extends the original real-time style transfer formulation by combining the features of several style images. This method successfully captures color information from the separate style images. The other aim of our project was to improve the temporal style continuity from frame to frame. Accordingly, we have experimented with the temporal stability of the output images and discussed the various available techniques that could be employed as alternatives.
CONGESTION CONTROL USING FUZZY BASED LSPS IN MULTIPROTOCOL LABEL SWITCHING NE...ijfcstjournal
In this paper, we have proposed a fuzzy based decision making component for high volume traffic MPLS
networks, by implementing Traffic Engineering, Quality of Service and Multipath routing. The approach
explicitly proves to be successful in solving the issues and challenges pertaining to stability, scalability in
high volume and dynamic traffic. Furthermore, it will work to handle congestion by higher link utilization
and provides efficient rerouting of traffic along with fault tolerance in the network. In this research work,
fuzzy calculations are done for fixing the attributes of the MPLS label(s), which is put on particular packet
representing the Forwarding Equivalence Class. Fuzzy controller consists of two sub fuzzy systems- Label
Switched Path setup System (LsS) and Traffic Splitting System (TSS). The computation of dynamic status of
Load and Delay is utilized by LsS to arrange the paths in preference order. The attained Link Capacity and
Utilization Rate are employing by TSS for maintaining congestion free path. The impact of this is to
facilitate, we have better decision making for splitting the traffic for different promising paths. This was
apparent from the series of traffic scenarios. Observations are obtained using this realization.
An Approach for Project Scheduling Using PERT/CPM and Petri Nets (PNs) ToolsIJMER
International Journal of Modern Engineering Research (IJMER) is Peer reviewed, online Journal. It serves as an international archival forum of scholarly research related to engineering and science education.
The development of embedded applications (such as Wireless Sensor Network protocols) often
requires a shift to formal specifications. To insure the reliability and the performance of the
WSNs, such protocols must be designed following some methods reducing error rate. Formal
methods (as Automata, Petri nets, algebra, logics, etc.) were largely used in the specification of
these protocols, their analysis and their verification. After that, their implementation is an
important phase to deploy, test and use those protocols in real environments. The main
objective of the current paper is to formalize the transformation from high-level specification (in
Timed Automata) to low-level implementation (in NesC language and TinyOs system) and to
automate such transformation. The proposed transformation approach defines a set of rules that
allow the passage between these two levels. We implemented our solution and we illustrated the
proposed approach on a protocol case study for the "humidity" and "temperature" sensing in
WSNs applications.
A BAYE'S THEOREM BASED NODE SELECTION FOR LOAD BALANCING IN CLOUD ENVIRONMENThiij
Cloud computing is a popular computing model as it renders service to large number of users request on
the fly and has lead to the proliferation of large number of cloud users. This has lead to the overloaded
nodes in the cloud environment along with the problem of load imbalance among the cloud servers and
thereby impacts the performance. Hence, in this paper a heuristic Baye's theorem approach is considered
along with clustering to identify the optimal node for load balancing. Experiments using the proposed
approach are carried out on cloudsim simulator and are compared with the existing approach. Results
demonstrates that task deployment performed using this approach has improved performance in terms of
utilization and throughput when compared to the existing approaches
PAGE: A Partition Aware Engine for Parallel Graph Computation1crore projects
IEEE PROJECTS 2015
1 crore projects is a leading Guide for ieee Projects and real time projects Works Provider.
It has been provided Lot of Guidance for Thousands of Students & made them more beneficial in all Technology Training.
Dot Net
DOTNET 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
7. IEEE based on parallel and distributed systems
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
7. IEEE based on parallel and distributed systems
ECE IEEE Projects 2015
1. Matlab project
2. Ns2 project
3. Embedded project
4. Robotics project
Eligibility
Final Year students of
1. BSc (C.S)
2. BCA/B.E(C.S)
3. B.Tech IT
4. BE (C.S)
5. MSc (C.S)
6. MSc (IT)
7. MCA
8. MS (IT)
9. ME(ALL)
10. BE(ECE)(EEE)(E&I)
TECHNOLOGY USED AND FOR TRAINING IN
1. DOT NET
2. C sharp
3. ASP
4. VB
5. SQL SERVER
6. JAVA
7. J2EE
8. STRINGS
9. ORACLE
10. VB dotNET
11. EMBEDDED
12. MAT LAB
13. LAB VIEW
14. Multi Sim
CONTACT US
1 CRORE PROJECTS
Door No: 214/215,2nd Floor,
No. 172, Raahat Plaza, (Shopping Mall) ,Arcot Road, Vadapalani, Chennai,
Tamin Nadu, INDIA - 600 026
Email id: 1croreprojects@gmail.com
website:1croreprojects.com
Phone : +91 97518 00789 / +91 72999 51536
Achieving Optimum Value of k in a K-fold Multicast Network with Buffer using ...cscpconf
Multicast network is widely used for effective communication, transmission and performance
optimizations of a network. In this paper, a new model has been developed to determine a
suitable value of the fold k of a k-fold multicast network under different traffic loads under
Poisson traffic with finite queue at each node. We have derived stationary distribution for the
network states and then derived expressions for the network throughput and the blocking
probability of the network. It has been found in this research work that the network throughput
increases very fast as we increase the fold number. However, at a certain value of the fold, the
blocking probability ceases to increase and it remains constant. We have also observed that as
the offered traffic is increased, the throughput also increases. Moreover, the system parameter k
is increased, the blocking probability decreases. However, after an optimum value of k, the
blocking probability remains constant for a particular value of the offered traffic. In fact, in this
paper, by evaluating the performance of a k-fold multicast network, our developed model improves the performance of a multicast network.
Enforcing end to-end proportional fairness with bounded buffer overflow proba...ijwmn
In this paper, we present a distributed flow-based
access scheme for slotted-time protocols, that prov
ides
proportional fairness in ad-hoc wireless networks u
nder constraints on the buffer overflow probabiliti
es at
each node. The proposed scheme requires local infor
mation exchange at the link-layer and end-to-end
information exchange at the transport-layer, and is
cast as a nonlinear program. A medium access contr
ol
protocol is said to be proportionally fair with res
pect to individual end-to-end flows in a network, i
f the
product of the end-to-end flow rates is maximized.
A key contribution of this work lies in the constru
ction of
a distributed dual approach that comes with low com
putational overhead. We discuss the convergence
properties of the proposed scheme and present simul
ation results to support our conclusions.
Optimal Configuration of Network Coding in Ad Hoc Networks1crore projects
IEEE PROJECTS 2015
1 crore projects is a leading Guide for ieee Projects and real time projects Works Provider.
It has been provided Lot of Guidance for Thousands of Students & made them more beneficial in all Technology Training.
Dot Net
DOTNET 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
7. IEEE based on parallel and distributed systems
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
7. IEEE based on parallel and distributed systems
ECE IEEE Projects 2015
1. Matlab project
2. Ns2 project
3. Embedded project
4. Robotics project
Eligibility
Final Year students of
1. BSc (C.S)
2. BCA/B.E(C.S)
3. B.Tech IT
4. BE (C.S)
5. MSc (C.S)
6. MSc (IT)
7. MCA
8. MS (IT)
9. ME(ALL)
10. BE(ECE)(EEE)(E&I)
TECHNOLOGY USED AND FOR TRAINING IN
1. DOT NET
2. C sharp
3. ASP
4. VB
5. SQL SERVER
6. JAVA
7. J2EE
8. STRINGS
9. ORACLE
10. VB dotNET
11. EMBEDDED
12. MAT LAB
13. LAB VIEW
14. Multi Sim
CONTACT US
1 CRORE PROJECTS
Door No: 214/215,2nd Floor,
No. 172, Raahat Plaza, (Shopping Mall) ,Arcot Road, Vadapalani, Chennai,
Tamin Nadu, INDIA - 600 026
Email id: 1croreprojects@gmail.com
website:1croreprojects.com
Phone : +91 97518 00789 / +91 72999 51536
MULTIUSER BER ANALYSIS OF CS-QCSK MODULATION SCHEME IN A CELLULAR SYSTEM ijwmn
In recent years, chaotic communication is a hot research topic and it suits better for the emerging wireless networks because of its excellent features. Different chaos based modulation schemes have evolved, of which the CS-DCSK modulation technique provides better BER performance and bandwidth
efficiency, due to its code domain approach. The QCSK modulation technique provides double benefit: higher data rate with similar BER performance and same bandwidth occupation as DCSK. By combining the advantage of code shifted differential chaos shift keying (CS-DCSK) and Quadrature chaos shift keying (QCSK) scheme, a novel modulation scheme called code shifted Quadrature chaos shift keying (CS-QCSK) is proposed and its suitability in a multiuser scenario is tested in this paper. The analytical expressions for the bit-error rate for Multi-user CS-QCSK scheme (MU-CS-QCSK) under Rayleigh
multipath fading channel is derived. The simulation result shows that, in multiuser scenario the proposed method outperforms classical chaotic modulation schemes in terms of bit error rate (BER).
Fuzzy Optimized Metric for Adaptive Network RoutingCSCJournals
Network routing algorithms used today calculate least cost (shortest) paths between nodes. The cost of a path is the sum of the cost of all links on that path. The use of a single metric for adaptive routing is insufficient to reflect the actual state of the link. In general, there is a limitation on the accuracy of the link state information obtained by the routing protocol. Hence it becomes useful if two or more metrics can be associated to produce a single metric that can describe the state of the link more accurately. In this paper, a fuzzy inference rule base is implemented to generate the fuzzy cost of each candidate path to be used in routing the incoming calls. This fuzzy cost is based on the crisp values of the different metrics; a fuzzy membership function is defined. The parameters of these membership functions reflect dynamically the requirement of the incoming traffic service as well as the current state of the links in the path. And this paper investigates how three metrics, the mean link bandwidth, queue utilization and the mean link delay, can be related using a simple fuzzy logic algorithm to produce a optimized cost of the link for a certain interval that is more „precise‟ than either of the single metric, to solve routing problem .
Performance Analysis for Parallel MRA in Heterogeneous Wireless NetworksEditor IJCATR
This paper analysis a different methods to find optimal path for services and power allocation to heterogeneous wireless network. Under heterogeneous wireless networks, a user can send data through a single or multi RATs (Radio Access Technology) simultaneously. The objective of this paper is to choose the optimal path for the services and power allocation to that bandwidth (BW) distributed joint allocation algorithm using Newton and modified Newton are adopted and the total system capacity compared. The analysis is done in Matlab and simulation results are compared. The numerical result shows that compare to Newton method, modified Newton method maximize the total system capacity.
PERFORMANCE FACTORS OF CLOUD COMPUTING DATA CENTERS USING [(M/G/1) : (∞/GDMOD...ijgca
The ever-increasing status of the cloud computing hypothesis and the budding concept of federated cloud computing have enthused research efforts towards intellectual cloud service selection aimed at developing techniques for enabling the cloud users to gain maximum benefit from cloud computing by selecting services which provide optimal performance at lowest possible cost. Cloud computing is a novel paradigm for the provision of computing infrastructure, which aims to shift the location of the computing infrastructure to the network in order to reduce the maintenance costs of hardware and software resources. Cloud computing systems vitally provide access to large pools of resources. Resources provided by cloud computing systems hide a great deal of services from the user through virtualization. In this paper, the cloud data center is modelled as queuing system with a single task arrivals and a task request buffer of infinite capacity.
Web Service QoS Prediction Approach in Mobile Internet Environmentsjins0618
Existing many Web service QoS prediction
approaches are very accurate in Internet environments,
however they cannot provide accurate prediction values in
Mobile Internet environments since QoS values of Web
services have great volatility. In this paper, we propose an
accurate Web service QoS prediction approach by weakening
the volatility of QoS data from Web services in Mobile Internet
environments. This approach contains three process, i.e., QoS
preprocessing, user similarity computing, and QoS predicting.
We have implemented our proposed approach with experiment
based on real world and synthetic datasets. The results show
that our approach outperforms other approaches in Mobile
Internet environments.
Device Discovery Schemes for Energy-Efficient Cluster Head Rotation in D2DTELKOMNIKA JOURNAL
In this paper, novel device discovery approaches for the cluster head rotation, which is a state-ofthe-
art method for the Device-to-Device communication, are proposed. The device discovery is the
process to detect and to include new devices in the Device-to-Device communication. The proposed
device discovery is aimed to attain energy efficiency for the communication devices. We propose two
schemes for the device discovery: eNB-assisted and independent device discovery. Compared to previous
work, the proposed device discovery is utilizing the cluster head rotation method, to achieve better energy
efficiency. In this work, several simulations were performed and discussed for both schemes. In the first
simulation, the device energy consumption is examined. After that, the number of devices that get rejected
is studied. The device discovery processes in multi cluster head scenario, which is cluster head rotation,
are examined in this paper. The result of the simulation shows that eNB-assisted device discovery can
provide better energy efficiency. Also, the number of rejected devices of the eNB-assisted device
discovery is slightly lower than independent device discovery.
AN EFFICIENT ALGORITHM FOR THE BURSTING OF SERVICE-BASED APPLICATIONS IN HYB...Nexgen Technology
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Mobile: 9751442511,9791938249
Telephone: 0413-2211159.
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Time Efficient VM Allocation using KD-Tree Approach in Cloud Server Environmentrahulmonikasharma
Cloud computing is an incipient and quickly evolving model, with new expenses and capabilities being proclaimed frequently. The increases of user on cloud with the expansion of variety of services, with that the complete allocation of resource with the minimum latent time for Virtual machine is necessary. To allocate this virtual cloud computing resources to the cloud user is a key technical issue because user demand is dynamic in nature that required dynamic allocation of resource too. To improve the allocation there must be a correct balanced algorithmic scheduling for Resource Allocation Technique. The aim of this work is to allocate resource to scientific experiment request coming from multiple users, wherever customized Virtual machines (VM) are aloft in applicable host out there in cloud. Therefore, properly programmed scheduling cloud is extremely vital and it’s significant to develop efficient scheduling methods for appropriately allocation of VMs into physical resource. The planned formulas minimize the time interval quality so as of O (Log n) by adopting KD-Tree.
Further Analysis Of A Framework To Analyze Network Performance Based On Infor...CSCJournals
Abstract In [1], Geng and Li presented a framework to analyze network performance based on information quality. In that paper, the authors based their framework on the flow of information from a Base Station (BS) to clients. The theory they established can, and needs, to be extended to accommodate for the flow of information from the clients to the BS. In this work, we use that framework and study the case of client to BS data transmission. Our work closely parallels the work of Geng and Li, we use the same notation and liberally reference their work. Keywords: information theory, information quality, network protocols, network performance
Style transfer aims to combine the content of one image with the artistic style of another. It was discovered that lower levels of convolutional networks captured style information, while higher levels captures content information. The original style transfer formulation used a weighted combination of VGG-16 layer activations to achieve this goal. Later, this was accomplished in real-time using a feed-forward network to learn the optimal combination of style and content features from the respective images. The first aim of our project was to introduce a framework for capturing the style from several images at once. We propose a method that extends the original real-time style transfer formulation by combining the features of several style images. This method successfully captures color information from the separate style images. The other aim of our project was to improve the temporal style continuity from frame to frame. Accordingly, we have experimented with the temporal stability of the output images and discussed the various available techniques that could be employed as alternatives.
CONGESTION CONTROL USING FUZZY BASED LSPS IN MULTIPROTOCOL LABEL SWITCHING NE...ijfcstjournal
In this paper, we have proposed a fuzzy based decision making component for high volume traffic MPLS
networks, by implementing Traffic Engineering, Quality of Service and Multipath routing. The approach
explicitly proves to be successful in solving the issues and challenges pertaining to stability, scalability in
high volume and dynamic traffic. Furthermore, it will work to handle congestion by higher link utilization
and provides efficient rerouting of traffic along with fault tolerance in the network. In this research work,
fuzzy calculations are done for fixing the attributes of the MPLS label(s), which is put on particular packet
representing the Forwarding Equivalence Class. Fuzzy controller consists of two sub fuzzy systems- Label
Switched Path setup System (LsS) and Traffic Splitting System (TSS). The computation of dynamic status of
Load and Delay is utilized by LsS to arrange the paths in preference order. The attained Link Capacity and
Utilization Rate are employing by TSS for maintaining congestion free path. The impact of this is to
facilitate, we have better decision making for splitting the traffic for different promising paths. This was
apparent from the series of traffic scenarios. Observations are obtained using this realization.
An Approach for Project Scheduling Using PERT/CPM and Petri Nets (PNs) ToolsIJMER
International Journal of Modern Engineering Research (IJMER) is Peer reviewed, online Journal. It serves as an international archival forum of scholarly research related to engineering and science education.
The development of embedded applications (such as Wireless Sensor Network protocols) often
requires a shift to formal specifications. To insure the reliability and the performance of the
WSNs, such protocols must be designed following some methods reducing error rate. Formal
methods (as Automata, Petri nets, algebra, logics, etc.) were largely used in the specification of
these protocols, their analysis and their verification. After that, their implementation is an
important phase to deploy, test and use those protocols in real environments. The main
objective of the current paper is to formalize the transformation from high-level specification (in
Timed Automata) to low-level implementation (in NesC language and TinyOs system) and to
automate such transformation. The proposed transformation approach defines a set of rules that
allow the passage between these two levels. We implemented our solution and we illustrated the
proposed approach on a protocol case study for the "humidity" and "temperature" sensing in
WSNs applications.
Cinnamons are a new computation model intended to form a theoretical foundation for Control Network Programming (CNP). CNP has established itself as a programming approach combining declarative and imperative features. It supports powerful tools for control of the computation process; in particular, these tools allow easy, intuitive, visual development of heuristic, nondeterministic, or randomized solutions. The paper providesrigorous definitions of the syntax and semantics of the new model of computation, at the same time trying to keep the intuition behind clear. The purposely simplified theoretical model is then compared to both WHILE-programs (thus demonstrating its Turing completeness), and the “real” CNP. Finally, future research possibilities are mentioned that would eventually extend the cinnamon programming and its theoretical foundation into the directions of nondeterminism, randomness and fuzziness.
Programming (CNP). CNP has established itself as a programming approach combining declarative and imperative features. It supports powerful tools for control of the computation process; in particular, these tools allow easy, intuitive, visual development of heuristic, nondeterministic, or randomized solutions. The paper providesrigorous definitions of the syntax and semantics of the new model of computation, at the same time trying to keep the intuition behind clear. The purposely simplified theoretical model is then compared to both WHILE-programs (thus demonstrating its Turing completeness), and the “real” CNP. Finally, future research possibilities are mentioned that would eventually extend the cinnamon programming and its theoretical foundation into the directions of nondeterminism, randomness and fuzziness.
From Simulation to Online Gaming: the need for adaptive solutions Gabriele D'Angelo
In many fields such as distributed simulation and online gaming the missing piece is adaptivity. There is a strong need for dynamic and adaptive solutions that can improve performances and react to problems.
SPEED-UP IMPROVEMENT USING PARALLEL APPROACH IN IMAGE STEGANOGRAPHYcsandit
This paper presents a parallel approach to improve the time complexity problem associated
with sequential algorithms. An image steganography algorithm in transform domain is
considered for implementation. Image steganography is a technique to hide secret message in
an image. With the parallel implementation, large message can be hidden in large image since
it does not take much processing time. It is implemented on GPU systems. Parallel
programming is done using OpenCL in CUDA cores from NVIDIA. The speed-up improvement
obtained is very good with reasonably good output signal quality, when large amount of data is
processed
Optimizer algorithms and convolutional neural networks for text classificationIAESIJAI
Lately, deep learning has improved the algorithms and the architectures of several natural language processing (NLP) tasks. In spite of that, the performance of any deep learning model is widely impacted by the used optimizer algorithm; which allows updating the model parameters, finding the optimal weights, and minimizing the value of the loss function. Thus, this paper proposes a new convolutional neural network (CNN) architecture for text classification (TC) and sentiment analysis and uses it with various optimizer algorithms in the literature. Actually, in NLP, and particularly for sentiment classification concerns, the need for more empirical experiments increases the probability of selecting the pertinent optimizer. Hence, we have evaluated various optimizers on three types of text review datasets: small, medium, and large. Thereby, we examined the optimizers regarding the data amount and we have implemented our CNN model on three different sentiment analysis datasets so as to binary label text reviews. The experimental results illustrate that the adaptive optimization algorithms Adam and root mean square propagation (RMSprop) have surpassed the other optimizers. Moreover, our best CNN model which employed the RMSprop optimizer has achieved 90.48% accuracy and surpassed the state-of-the-art CNN models for binary sentiment classification problems.
Building a new CTL model checker using Web Servicesinfopapers
Florin Stoica, Laura Stoica, Building a new CTL model checker using Web Services, Proceeding The 21th International Conference on Software, Telecommunications and Computer Networks (SoftCOM 2013), At Split-Primosten, Croatia, 18-20 September, pp. 285-289, 2013
DOI=10.1109/SoftCOM.2013.6671858 http://dx.doi.org/10.1109/SoftCOM.2013.6671858
A Metamodel and Graphical Syntax for NS-2 ProgramingEditor IJCATR
One of the most important issues, around the world, which manufacturers pay special attention to is to promote their
activities in order to be able to give high quality products or services. Perhaps the first advice to achieve this goal is simulation idea.
Therefore, simulation software packages with different properties have been made available. One of the most applicable simulators is
NS-2 which suffers from internal complexity. On the other hand, Domain Specific Modeling Languages can make an abstraction level
by which we can overcome the complexity of NS-2, increase the production speed, and promote efficiency. So, in this paper, we
introduce a Domain Specific Metamodel for NS-2.This new metamodel paves the ways for introducing abstract syntax and modeling
language syntax. In addition, created syntax in Domain Specific Modeling Language is supported by a graphical modeling tool.
An efficient tree based self-organizing protocol for internet of thingsredpel dot com
An efficient tree based self-organizing protocol for internet of things.
for more ieee paper / full abstract / implementation , just visit www.redpel.com
Privacy preserving and delegated access control for cloud applicationsredpel dot com
Privacy preserving and delegated access control for cloud applications
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Performance evaluation and estimation model using regression method for hadoo...redpel dot com
Performance evaluation and estimation model using regression method for hadoop word count.
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Frequency and similarity aware partitioning for cloud storage based on space ...redpel dot com
Frequency and similarity aware partitioning for cloud storage based on space time utility maximization model.
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Multiagent multiobjective interaction game system for service provisoning veh...redpel dot com
Multiagent multiobjective interaction game system for service provisoning vehicular cloud
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Efficient multicast delivery for data redundancy minimization over wireless d...redpel dot com
Efficient multicast delivery for data redundancy minimization over wireless data centers
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Cloud assisted io t-based scada systems security- a review of the state of th...redpel dot com
Cloud assisted io t-based scada systems security- a review of the state of the art and future challenges.
for more ieee paper / full abstract / implementation , just visit www.redpel.com
I-Sieve: An inline High Performance Deduplication System Used in cloud storageredpel dot com
I-Sieve: An inline High Performance Deduplication System Used in cloud storage
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Architecture harmonization between cloud radio access network and fog networkredpel dot com
Architecture harmonization between cloud radio access network and fog network
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A tutorial on secure outsourcing of large scalecomputation for big dataredpel dot com
A tutorial on secure outsourcing of large scalecomputation for big data
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A parallel patient treatment time prediction algorithm and its applications i...redpel dot com
A parallel patient treatment time prediction algorithm and its applications in hospital.
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Unit 8 - Information and Communication Technology (Paper I).pdfThiyagu K
This slides describes the basic concepts of ICT, basics of Email, Emerging Technology and Digital Initiatives in Education. This presentations aligns with the UGC Paper I syllabus.
How to Create Map Views in the Odoo 17 ERPCeline George
The map views are useful for providing a geographical representation of data. They allow users to visualize and analyze the data in a more intuitive manner.
Synthetic Fiber Construction in lab .pptxPavel ( NSTU)
Synthetic fiber production is a fascinating and complex field that blends chemistry, engineering, and environmental science. By understanding these aspects, students can gain a comprehensive view of synthetic fiber production, its impact on society and the environment, and the potential for future innovations. Synthetic fibers play a crucial role in modern society, impacting various aspects of daily life, industry, and the environment. ynthetic fibers are integral to modern life, offering a range of benefits from cost-effectiveness and versatility to innovative applications and performance characteristics. While they pose environmental challenges, ongoing research and development aim to create more sustainable and eco-friendly alternatives. Understanding the importance of synthetic fibers helps in appreciating their role in the economy, industry, and daily life, while also emphasizing the need for sustainable practices and innovation.
Students, digital devices and success - Andreas Schleicher - 27 May 2024..pptxEduSkills OECD
Andreas Schleicher presents at the OECD webinar ‘Digital devices in schools: detrimental distraction or secret to success?’ on 27 May 2024. The presentation was based on findings from PISA 2022 results and the webinar helped launch the PISA in Focus ‘Managing screen time: How to protect and equip students against distraction’ https://www.oecd-ilibrary.org/education/managing-screen-time_7c225af4-en and the OECD Education Policy Perspective ‘Students, digital devices and success’ can be found here - https://oe.cd/il/5yV
How to Make a Field invisible in Odoo 17Celine George
It is possible to hide or invisible some fields in odoo. Commonly using “invisible” attribute in the field definition to invisible the fields. This slide will show how to make a field invisible in odoo 17.
2024.06.01 Introducing a competency framework for languag learning materials ...Sandy Millin
http://sandymillin.wordpress.com/iateflwebinar2024
Published classroom materials form the basis of syllabuses, drive teacher professional development, and have a potentially huge influence on learners, teachers and education systems. All teachers also create their own materials, whether a few sentences on a blackboard, a highly-structured fully-realised online course, or anything in between. Despite this, the knowledge and skills needed to create effective language learning materials are rarely part of teacher training, and are mostly learnt by trial and error.
Knowledge and skills frameworks, generally called competency frameworks, for ELT teachers, trainers and managers have existed for a few years now. However, until I created one for my MA dissertation, there wasn’t one drawing together what we need to know and do to be able to effectively produce language learning materials.
This webinar will introduce you to my framework, highlighting the key competencies I identified from my research. It will also show how anybody involved in language teaching (any language, not just English!), teacher training, managing schools or developing language learning materials can benefit from using the framework.
Instructions for Submissions thorugh G- Classroom.pptxJheel Barad
This presentation provides a briefing on how to upload submissions and documents in Google Classroom. It was prepared as part of an orientation for new Sainik School in-service teacher trainees. As a training officer, my goal is to ensure that you are comfortable and proficient with this essential tool for managing assignments and fostering student engagement.
Overview on Edible Vaccine: Pros & Cons with Mechanism
Validation of pervasive cloud task migration with colored petri net
1. TSINGHUA SCIENCE AND TECHNOLOGY
ISSNll1007-0214ll08/10llpp89-101
Volume 21, Number 1, February 2016
Validation of Pervasive Cloud Task Migration with Colored Petri Net
Lianzhang Zhu, Shouchao Tan, Weishan Zhang , Yong Wang, and Xiwei Xu
Abstract: Mobile devices are resource-limited, and task migration has become an important and attractive feature
of mobile clouds. To validate task migration, we propose a novel approach to the simulation of task migration in a
pervasive cloud environment. Our approach is based on Colored Petri Net (CPN). In this research, we expanded
the semantics of a CPN and created two task migration models with different task migration policies: one that took
account of context information and one that did not. We evaluated the two models using CPN-based simulation
and analyzed their task migration accessibility, integrity during the migration process, reliability, and the stability of
the pervasive cloud system after task migration. The energy consumption and costs of the two models were also
investigated. Our results suggest that CPN with context sensing task migration can minimize energy consumption
while preserving good overall performance.
Key words: colored Petri net; task migration; pervasive cloud; context information; validation
1 Introduction
In mobile cloud computing, the resource limitations of
mobile devices sometimes mean that their computing
and storage capabilities are insufficient for task
execution[1]
. Task migration has therefore become
an extremely important challenge. Many researchers
have investigated mobile cloud computing or cloud
computing task migration[2,3]
.
As early as 1988, Schwederski et al.[2]
conducted
research on a task migration model in a parallel
processing system. They focused on task migration
costs, which consist of directed and undirected
overheads and migration penalties. The directed
overhead encompasses the cost of moving a task
Lianzhang Zhu, Shouchao Tan, Weishan Zhang,
and Yong Wang are with Department of Software
Engineering, China University of Petroleum, No. 66
Changjiang West Road, Qingdao 266580, China. E-mail:
zhulz@upc.edu.cn; tansc.upc@foxmail.com; zhangws@
upc.edu.cn; wangyongsdlx@gmail.com.
Xiwei Xu is with Software Systems Research Group, NICTA,
Sydney, Australia. E-mail: xiwei.xu@nicta.com.au.
To whom correspondence should be addressed.
Manuscript received: 2015-10-15; revised: 2015-11-04;
accepted: 2015-12-06
when no other tasks affect the migration, while the
undirected overhead is the additional time needed
for migration due to the influence of other tasks. A
migration penalty may be incurred when the migration
affects other tasks. The authors proposed a model for
parameterizing migration costs in a parallel processing
system. A prototype that enabled adaptive application
task migration in a Grid environment was presented[4]
.
The prototype automatically reconfigures distributed
applications in response to network performance
failures and Denial of Service (DoS) attacks. The
use of performance monitoring software enables
network connection failover and automatic application
task migration within a heterogeneous distributed
computing environment. Ma and Wang[3]
proposed a
Java bytecode transformation technique for realizing
task migration without imposing significant overheads
on normal execution. An asynchronous migration
technique allows migrations to take place virtually
anywhere in the user codes, and the proposed Twin
Method Hierarchy minimizes the overhead resulting
from state-restoration codes in normal execution.
Buchbinder et al.[5]
proposed a novel Efficient Online
Algorithm to solve the migration problem of batch jobs
between datacenters. The algorithm has two distinctive
www.redpel.com +917620593389
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2. 90 Tsinghua Science and Technology, February 2016, 21(1): 89-101
features: it considers future variability and uncertainty
of energy sources, and it can handle the fundamental
tradeoff between energy and the bandwidth costs of
migrating application data and states.
Most existing work on task migration focuses
on identifying ways of achieving task migration by
constructing models or infrastructure. Other works have
focused on migration policies and deriving algorithms
that can solve certain task migration challenges. To
the best of our knowledge, no analysis has been made
of the following topics: when to start task migration,
the integrity of task migration, or the reliability and
stability of a mobile cloud platform after task migration.
These issues are key to task migration in mobile cloud
computing, as they help determine the appropriateness,
feasibility, and performance of task migration. In this
paper, we propose a new approach to validation of
task migration in a mobile cloud. We expanded the
semantics of the Colored Petri Net (CPN) to include
description of contexts and the relationships between
the CPU usage, memory usage rate, and network
bandwidth of the system. For task migration, we created
two task migration models with different task migration
rules based on the semantic expanded CPN and drawing
on the concept and composition of the OSGi-based
pervasive cloud platform. We then simulated and
verified the two models of task migration. Based on
the data obtained from simulation, we undertook a
comprehensive evaluation, including: task migration
accessibility, integrity of the task migration process, and
the reliability and stability of the mobile cloud system
after task migration. We also compared the energy
consumption of the two models.
The rest of paper is organized as follows. Section
2 presents some preliminaries, including a CPN
description and definition, one CPN ML tool, an
overview of task migration, and the OSGi-PC pervasive
cloud infrastructure. Section 3 extends the semantic of
the original CPN and gives a detailed description of
our CPN-based task migration models. In Section 4,
we introduce the simulation of the proposed migration
models with CPN Tools. Evaluation and analysis of our
proposed task migration models are given in Section 5.
The conclusions and plans for future work in Section 6
end the paper.
2 Preliminaries
2.1 CPN
CPN is a language developed by Jensen[6]
. It is an
extension of the basic Petri Net (PN), which is used
to model and analyze parallel systems. CPN uses the
same model elements as PN, but adds properties to
distinguish between different individuals of the same
type of a system factor[7]
. The properties of the model
elements are referred to as “colors”. A formal definition
of CPN is as follows:
CPN D .˙; P; T; A; N; C; G; E; I),
where
(1) ˙ is a finite set of data types that is called a color
set;
(2) P is a finite set of places;
(3) T is a finite set of transitions;
(4) A is a finite set of arcs, and P T D P A D
T A D ∅;
(5) N is a node set function, N W A ! P T [T P ;
(6) C is a color set function that assigns a color set to
one place, C W P ! ˙;
(7) G is a guard function or transition expression
function that is defined as T ! Expression;
(8) E is an arc expression function that assigns an
arc expression to each arc. The definition is E W A !
Expression; and
(9) I is an initialization function that assigns an
initialization expression to each place.
CPN differs from PN in two ways: all places and
transitions have color attributes, and the input and
output are matrices, whereas in PN, they are scalars.
In CPN, a token may have a complex data type, as in
a programming language, and transitions can process
the values of the received tokens and create new ones,
which can be of different data types. CPN has better
modeling than PN.
2.2 CPN tools
CPN is supported by a standard ML[8]
with a CPN ML
tool, which is an extension of the ML language[9]
. This
tool can be used to create a CPN model and allocate
color sets, variables, and functions. Most importantly,
functions can be used at arc expression and guards in
the CPN model.
CPN Tools can help to construct places, transitions,
and functions and automatically check grammar. It
includes a simulation tool, a state space tool, and a
constructing tool. Users can run simulations of the
system and analyze the state space using CPN Tools.
After the simulation, we obtain the step number, time,
and statement of the system model.
Figure 1 shows samples of the ML syntax used in
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3. Lianzhang Zhu et al.: Validation of Pervasive Cloud Task Migration with Colored Petri Net 91
Fig. 1 Samples of ML syntax used in CPN Tools.
CPN Tools. A color set is declared using the key word
“colset”, whereas a variable is declared using the key
word “var”. At the end of the figure, there are two
functions that are declared using the keyword “fun”.
The CPN Tools version 4.0 interface is shown in
Fig. 2.
2.2.1 Simulation tool of CPN Tools 4.0
When a model is constructed, CPN Tools 4.0 will
automatically check grammar. If no errors are found,
the simulation can be executed. The simulation tool is
shown in Fig. 3. We can use it to rewind, stop, and
debug the simulation and to produce a simulation report
with the correct setting to index options.
Fig. 2 Interface of CPN Tools 4.0.
Fig. 3 Simulation tool of CPN Tools 4.0.
2.2.2 State space tool of CPN Tools 4.0
A state space tool can help analyze the states of
the system model. A label can be created for each
accessible node. All binding elements from the start
to end nodes form a state space graph. The state
space tool can calculate the state space of the model,
produce a connected graph of the state space, and output
an attribute report to help analyze the accessibility,
boundedness, activity, and fairness of the model. This
allows the performance of the model to be evaluated.
2.3 Task migration and OSGi-based pervasive
cloud
Resource-limited devices or systems often need to
offload computational or resource-intensive tasks to
cloud nodes[10]
. This is called task migration. In
this research, we used an OSGi-based pervasive
cloud (OSGi-PC) infrastructure as the mobile cloud
platform because OSGi-PC[11]
can exploit both the
cloud computing capabilities and component flexibility
of OSGi[12]
. It is easy to model task migrations
based on the concepts and structure of OSGi-PC,
and OSGi-based frameworks are widely used for both
small devices and powerful cloud nodes. All these
services follow the same OSGi standard, which offers
inter-operability, support for dynamic deployment and
replacement of OSGi services, and scalability when
new services are added. An overview of OSGi-PC
is presented in Fig. 4. Using the coordination of
the discovery component, both remote cloud service
frameworks and local client service frameworks can be
accessed.
Fig. 4 Overview of OSGi-PC.
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4. 92 Tsinghua Science and Technology, February 2016, 21(1): 89-101
3 CPN-Based Task Migration Model
In an actual pervasive cloud, the task migration
system is very complicated because it involves mobile
components, servers, virtual machines, networks, and
others. Thus, before constructing the task migration
system model, we made assumptions as follows.
(1) All entity information of task data packages
delivered among virtual machines though the network
is related to task type.
(2) When assessing system performance, only virtual
machines in servers and mobile devices need to be
considered. It is unnecessary to pay attention to the
implementation of the bottom protocol.
As shown in Fig. 5, the overall working flow of
our validation approach is as follows: obtain context
information from OSGi-PC, expand the semantics of
CPN, construct the task migration model by applying
two migration policies, and finally, simulate the two
models and compare their performance.
3.1 CCPN: CPN with context sensing
Task migration needs to integrate context information,
but CPN has weak semantics that can not support this.
Therefore, we introduced a semantically expanded CPN
called CPN with context sensing (CCPN). We used
CCPN to integrate context with our task migration
model.
A formal definition of CCPN is as follows:
CCPN D .˙; P; T; F; Fi; M0/;
where
(1) ˙ is a set of data types, also called color sets;
(2) P D Pc [ Pt when Pc is a finite set of context
Fig. 5 Overall technology route.
places and Pt is a finite set of temporary places;
(3) T D Ti [ Te when Ti is a finite set of internal
transitions and Te is a finite set of external transitions;
(4) F is a finite set of arcs, and P T D P F D
T F D ∅;
(5) Fi is a finite set of restraining arcs; and
(6) M0 is the initial state.
For clarity, Fig. 6 presents context places, temporary
places, internal transitions, internal clean transitions,
and external transitions in CCPN.
3.2 CCPN TM: CCPN-based task migration
model
Using semantically expanded CCPN, we can construct
a task migration model called CCPN TM to model task
migration in pervasive cloud computing, taking OSGi-
PC as the platform.
CCPN TM D .Phost; Pvm; Pmobile; T; ˙cloud; R/,
where
(1) Phost represents the servers;
(2) Pvm represents virtual machines in the servers;
(3) Pmobile represents mobiles in pervasive
computing;
(4) T represents all actions in a pervasive computing
environment;
(5) ˙cloud represents all color sets in this model; and
(6) R represents two task migration policies: one
with no context, and one with context information.
Figure 7 shows the CCPN-based task migration
Fig. 6 Graphical representation of places and transitions in
CCPN.
Fig. 7 CCPN-based task migration model.
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5. Lianzhang Zhu et al.: Validation of Pervasive Cloud Task Migration with Colored Petri Net 93
model, where the solid-line arrows indicate pervasive
cloud servers that are accessible and the dashed-line
arrows indicate task migration policies among servers.
3.2.1 Task migration policies
Figure 8 shows the first model without context
information. In this approach, task migration is
determined by state of virtual machines where the tasks
are located. There are two state values: “task in” and
“task out”. Only a virtual machine whose “task out”
value is “true” can migrate its tasks out to other virtual
machines, and only a virtual machine whose “task in”
is “true” can accept tasks from other virtual machines.
The two state values are declared in the VirtualMachine
color set. The functions “TaskMigrationOut” and
“TaskMigrationIn” are used to change the state of the
virtual machines.
The second task migration approach integrates the
context information, as shown in Fig. 9. In contrast
to the approach without context, this policy makes
migration decisions based on not only the two
state values of the virtual machines but also the
context information, which includes the CPU, RAM,
and bandwidth of the machines. A function named
“fusioncontext” determines whether the context of a
Fig. 8 Task migration policy without context information.
Fig. 9 Task migration policy with context sensing.
virtual machine is suitable to task migration.
The CCPN TM model uses many data types, the
most important of which are “Host”, “Mobile”,
“VirtualMachine”, and “Task”. Our color sets were
defined as shown in Fig. 10. “Host” covers many
attributes such as CPU, memory, and energy
consumption. Many virtual machines may run
on a single host, and each virtual machine may
perform multiple tasks. The key attributes of virtual
machines include CPU, memory, bandwidth, energy
consumption, costs, and task migration policies.
“Mobile” covers similar attributes to “Host” while
whereas “Task” covers attributes such as size, state, and
decision of whether to migrate.
3.2.2 Task execution and migration target selection
We used the function “process” to deal with task
execution in the original virtual machine and after
migration to another virtual machine, as shown in
Fig. 11.
When a migration policy is selected, another
important aspect of task migration is the selection of a
new virtual machine for tasks that need to be migrated.
We selected the migration-in virtual machine using the
match degree, as shown in Fig. 12. We describe this
selection algorithm in Section 4.
4 Simulation to CCPN TM with CPN Tools
4.0
To evaluate and analyze the task migration model
described in Section 3, we implemented and simulated
the models using our semantic expanded CCPN, as
defined in Section 3.1.
4.1 Top level module of task migration
The top module of task migration model was built with
CPN Tools 4.0, and is shown in Fig. 13. This module
included a Mobile Center module, a Net Transmit
module, and a Data Center Broker module, described
with substitution transition. The Mobile Center module
made the preparations for task migration, and then
transferred the task to the Net Transmit module,
which provided the net transmit functions. Tasks to
Fig. 10 Color set definition of Host, Mobile, VirtualMachine, and Task.
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6. 94 Tsinghua Science and Technology, February 2016, 21(1): 89-101
Fig. 11 Task execution function definited with CPN Tools.
Fig. 12 Target selection function of task migration.
Fig. 13 Top module of task migration with CPN Tools 4.0.
be migrated were passed to the Data Center Broker
for execution. When the task execution completed, it
was transmitted to place “Result”. If further migration
was needed, it was migrated to place “ReMigrate”, and
then transmitted to the Data Center Broker through the
“ProceessTask” transition.
In the task migration model, substitution transitions
and places were connected with directed arcs,
representing the data transmission channel. When the
task migration system was initiated, virtual machines
prepared the tasks that needed to be migrated. The tasks
were then transferred to the “UserTask” list in the output
place. Thereafter, CPN Tools sent the tasks to the Net
Transmit module, which then selected suitable virtual
machines, executed the tasks, and determined whether
the current tasks needed secondary migration.
4.2 Mobile Center module
The Mobile Center module is shown in Fig. 14. It was
mainly used to trigger the execution of the model, do
pre-processing of the tasks in the mobiles, and transfer
the tasks awaiting migration to the “UserTasks” place.
To illustrate the preparation needed before task
migration, an example in which each cluster contains
only two or three mobiles is shown in Fig. 15. Tasks
need to be migrated when the utilization ratio of
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7. Lianzhang Zhu et al.: Validation of Pervasive Cloud Task Migration with Colored Petri Net 95
Fig. 14 Mobile Center module of task migration with CPN Tools 4.0.
Fig. 15 Pre-process of tasks to be migrated in mobile device.
CPU and RAM in the mobiles is high. The status
of unfinished tasks is changed from “Running” to
“Suspend”. All the tasks with “Suspend” status are
transferred to the “UserTask” place to await migration.
4.3 Net Transmit module
The Net Transmit module (Fig. 16) had two input
variables “n” and “transmit”, which were used to
control the transfer order of the task data packets.
Output place “A” was used to migrate the tasks to the
Data Center Broker module, while output place “C”
was used to determine whether the Data Center Broker
would take the next packet.
4.4 Data Center Broker module
After the tasks to be migrated were transferred from the Fig. 16 Net Transmit module of task migration model.
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8. 96 Tsinghua Science and Technology, February 2016, 21(1): 89-101
Net Transmit module to the Data Center Broker module,
the Broker sent the tasks to the data centers. The
centers then selected the most suitable virtual machine
for the task based on the machine’s CPU and RAM.
If the task execution was completed in the Process
module, it was sent to the “Result” place, whereas
tasks needing secondary migration were sent to the Data
Center Broker again through the “ReMigrate” place.
This process is as shown in Fig. 17. We can see that
this module had three important functions. The first
was target selection, which we discuss in Section 3.2.2.
The second was the task execution. The third function
applied context information. We now discuss these
three functions.
In a pervasive cloud environment, there are many
virtual machines in each datacenter. A key challenge
is the selection of the most suitable virtual machine to
complete the tasks with minimum cost and maximum
resource release. If more than one task needs to be
migrated, and the best virtual machines for these tasks
are selected simultaneously, a clustering effect may be
incurred. To avoid this, whilst balancing the workload
of the virtual machines, we selected the target node
based on probabilities, rather than by migrating tasks
to the virtual machine with the best performance.
CPU and RAM were considered in target selection, as
follows:
(1) Select n targets from the pervasive cloud using
the matching degree URavailable of the target virtual
machines and the URcost of the task.
(2) Construct a probability model based on the
Ravailable value of the n targets.
The probability that the virtual machine would accept
the task was then defined by Formula (1).
pi D URi =.†n
1URi / (1)
where URi D Ci Ri , while Ci represents the
utilization rate of CPU and Ri represents the utilization
rate of RAM in the virtual machines.
(3) Randomly generate a number [0, 1] and compare
it with the probability value in the second step to
determine the task migration target.
A task migration model without context determines
whether to migrate based only on the state of the
virtual machines. In contrast, our context fusion model
applied statistical methods to the CPU utilization, RAM
utilization, and bandwidth of the virtual machine in
runtime, improving the accuracy of task migration. The
context information was saved in the “CPURAMBW”
place, as shown in Fig. 18. The function “judge”
determined if the virtual machine could provide
sufficient CPU, RAM, and bandwidth to support the
execution of tasks, as shown in Fig. 19.
5 Evaluation and Analysis
In the previous sections, we have described the task
migration models and established a multi-level task
migration model using CPN Tools. We then wished
to confirm the correctness of the model by showing
that the model could describe the task migration system
correctly. In this section, we present an analysis of task
migration by our two different migration models in a
pervasive cloud, using a combination of state space and
monitor in CPN Tools 4.0.
5.1 Model evaluation
The task migration model built with CPN Tools 4.0 and
based on CCPN provided the basis for demonstrating
the logic and effectiveness of task migration. The
simulation result report and state space report from
the simulation were used to construct a state space
graph. This allowed analysis of the features of the task
migration model.
Fig. 17 Data Center Broker module.
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9. Lianzhang Zhu et al.: Validation of Pervasive Cloud Task Migration with Colored Petri Net 97
Fig. 18 Context information fusion with CPN Tools 4.0.
Fig. 19 Function “judge”.
A partial simulation report is as shown in Fig. 20.
From the whole simulation report, we could check
that the number of tokens in each place did not
exceed the initial task number, proving that the model
was bounded. We conducted simulations of the task
Fig. 20 A partial simulation report.
migration model CCPN TM, and demonstrated that
the model could complete its execution in finite steps,
which confirmed the activity of our model. As can be
seen from Fig. 21, there were 12 tokens in the place
“Result”. This is the correct output, which indicates
that our model is performed correctly.
5.2 State space analysis—Accessibility and
activity
The state space report was used to demonstrate the
accessibility and activity of the CCPN TM model. A
partial state space report is shown in Fig. 22.
Figure 23 shows part of the state accessibility
graph of task migration, with a detailed description of
each node. Each node in the state accessibility graph
represents an arrival identification, and each directed
arc represents a binding element from source node to
target node. From the figure we can check that the
virtual machines are able to access each other in a
task migration system. The task migration routes also
confirmed the accessibility of our task migration model.
5.3 Energy consumption analysis
We declared the “Host” color set in the CCPN TM
task migration model, and in this color set the
energy consumption was defined. Using simulation,
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Fig. 21 Result activity.
Fig. 22 A part of the state space report.
we could obtain the energy consumption of servers
in the pervasive cloud. Before analyzing the energy
consumption of task migration, we first made the
following assumptions, following earlier studies[13,14]
.
(1) Task migration from one virtual machine to
another will generate costs that reflect the size of the
task and the bandwidth. Migration time is the main
computing parameter in the task migration cost, and can
be calculated using Formulas (2) and (3).
MigrationTime D Task size/Bandwidth available (2)
(2) Estimation of the energy consumption of servers
defined in the color set “Host” can be calculated by the
energy consumption model defined with the following
Formula (3):
Ei D minEi C CPU Sagei .maxEi minEi /C
.†MigrationTime/ Power (3)
where Ei represents consumption (per hour in Watts)
for the servers, CPU Sagei is the average value of
the utilization rate of the virtual machines running in
the servers, maxEi represents the maximum energy
consumption when the server is at maximum load, and
minEi represents the energy consumption when the
server is in the idle state. Power represents the energy
consumption value of the unit time to transfer tasks.
†MigrationTime represents the total time consumption
of all task migration in the server.
(3) Task migration is without delay. Task execution
cost was represented by ECost, calculated using
Formula (4), and the cost of task migration between
virtual machines was represented by TCost, calculated
using Formula (5).
ECost D .†vmEC/ Price.P / (4)
TCost D †vmMigrationTime Price(SLAmin/ (5)
In Formula (4), Price(P) represents the equipment
price in the cloud environment, and EC represents the
virtual machine energy consumption. In Formula (5),
Price(SLAmin) represents the lowest price of the Service
Level agreement and is usually fixed in a pervasive
cloud. †vmMigrationTime means the total migration
time for migrating tasks from one virtual machine to
others in the server.
These formulas gave the energy consumption of task
migration. To improve accuracy, we averaged energy
consumption, execution cost, and transmission cost
from multiple simulations.
We selected five hosts in our pervasive cloud
environment. The average power consumption of the
two task migration models is shown in Fig. 24.
Comparison of the two lines showed that the energy
consumption of the migration model without context
information was greater than that of the context sensing
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11. Lianzhang Zhu et al.: Validation of Pervasive Cloud Task Migration with Colored Petri Net 99
Fig. 23 State accessibility graph of task migration.
Fig. 24 Average energy consumption of two task migration
models.
task migration model. This is because the latter model
factored in the state and current context of the virtual
machine, allowing the virtual machine with the most
appropriate CPU and RAM to process the task to be
selected, while the former considered only the state of
the virtual machine.
The average execution costs of the two task migration
models across the five hosts are shown in Fig. 25.
In most cases the context sensing task migration
model achieved a lower cost, because it considered the
performance of the virtual machines when selecting the
migration target.
Fig. 25 Average operating costs of two task migration
models.
Although the task migration model with context
sensing reduced energy consumption, it could have
higher transmission costs (Fig. 26).
6 Conclusions and Future Work
In this paper, we proposed a context enabled
CPN approach to validating task migration in a
pervasive cloud environment. Our research evaluated
task migration accessibility, integrity during the task
migration process, and the energy consumption of
the mobile cloud system during task migration. We
analyzed the CPU, RAM, and bandwidth of both
hosts and virtual machines, in terms of task size, task
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12. 100 Tsinghua Science and Technology, February 2016, 21(1): 89-101
Fig. 26 Average transmission costs of two task migration
models.
state, and other contexts. We built two CCPN-based
task migration models with different task migration
policies. CPN Tools 4.0 was then used to evaluate
the activity and accuracy of the systems, and to
analyze the energy consumption and costs of the two
models. The simulation results suggest that CCPN-
based task migration can combine energy consumption
minimization with good overall performance.
In future research we will also consider the time
parameter of task execution, to determine whether
task migration should be done or not. We currently
select the target virtual machine for task migration
by matching virtual machines and tasks, but in real
applications, the location of the virtual machines is
also an important selection factor. Adding this to the
selection function could further improve the accuracy
of the task migration model, while reducing energy
consumption and migration costs.
References
[1] M. D. Kristensen, Empowering mobile devices through
cyber foraging, PhD dissertation, Department of Computer
Science, Aarhus University, 2010.
[2] T. Schwederski, H. J. Siegel, and T. L. Casavant, A
model of task migration in partitionable parallel processing
systems, in Frontiers of Massively Parallel Computation,
1988. Proceedings, 2nd Symposium on the Frontiers of,
Fairfax, VA, 1988, pp. 211–214.
[3] R. K. K. Ma and C. L. Wang, Lightweight application-level
task migration for mobile cloud computing, in Advanced
Information Networking and Applications (AINA), 2012
IEEE 26th International Conference on, Fukuoka, Japan,
2012, pp. 550–557.
[4] S. Frechette and D. R. Avresky, Method for task
migration in grid environments, in Network Computing
and Applications, Fourth IEEE International Symposium
on, Cambridge, MA, USA, 2005, pp. 49–58.
[5] N. Buchbinder, N. Jain, and I. Menache, Online job-
migration for reducing the electricity bill in the cloud, in
NETWORKING 2011 Springer. Springer, 2011, pp. 172–
185.
[6] K. Jensen, Coloured Petri Nets: Basic Concepts, Analysis
Methods and Practical Use. Springer Science & Business
Media, 2013.
[7] Z. Hu, T. Lu, and Z. Zhao, Context-aware service system
modeling using timed CPN, in Service Systems and
Service Management (ICSSSM), 2013 10th International
Conference on, Hong Kong, China, 2013. pp. 164–169.
[8] A. W. Appel and D. B. MacQueen, Standard ML of new
jersey, in Programming Language Implementation and
Logic Programming. Springer Berlin Heidelberg, 1991,
pp. 1–13.
[9] A. V. Ratzer, L. Wells, H. M. Lassen, M. Laursen, J. F.
Ovortrup, M. S. Stissing, M. Westergaard, S. Christensen,
and K. Jensen, CPN tools for editing, simulating, and
analysing coloured Petri nets, in Applications and Theory
of Petri Nets 2003. Springer Berlin Heidelberg, 2003, pp.
450–462.
[10] M. Shiraz and A. Gani, A lightweight active service
migration framework for computational offloading in
mobile cloud computing, The Journal of Supercomputing,
vol. 68, no. 2, pp. 978–995, 2014.
[11] W. S. Zhang, L. C. Chen, X. Liu, Q. H. Lu, P. Y. Zhang,
and Y. Su, An OSGi based adaptive and flexible pervasive
cloud infrastructure, Science China Information Science,
vol. 53, no. 3, pp. 1–11, 2014.
[12] O. S. G. Alliance, OSGi—The dynamic module system for
Java, http://www.osgi.org/, 2009.
[13] M. M. Alansari and B. Bordbar, An architectural
framework for enforcing energy management policies in
cloud, in 2013 IEEE Sixth International Conference on
Cloud Computing, Santa Clara, CA, USA, 2013, pp. 717–
724.
[14] P. Aziz Abdulla and R. Mayr, Petri nets with time and cost,
arXiv preprint arXiv: 1302.3291, 2013.
Lianzhang Zhu is a professor in China
University of Petroleum. He graduated
from East China Petroleum Institute, and
received a bachelor degree in science.
In 1988, he graduated from Shenyang
Institute of computing technology, Chinese
Academy of Sciences with a master’s
degree in engineering. He got his PhD
degree in mineral and general survey from China University
of Petroleum in 2003. He has visited Science and Technology
University of Missouri. His main research interests are software
performance evaluation, software testing, oil field data model,
etc.
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13. Lianzhang Zhu et al.: Validation of Pervasive Cloud Task Migration with Colored Petri Net 101
Shouchao Tan is a master student working
on big data processing and software
architecture. She graduated from China
University of Petroleum with a bachelor
degree in 2014. She has published 3 papers
on pervasive cloud computing and decision
making for task migration in pervasive
cloud.
Weishan Zhang is a full professor,
deputy head for research of Department of
Software Engineering, School of Computer
and Communication Engineering, China
University of Petroleum. He got his PhD
degree from Northwestern Polytechnical
University in 2001. His research interests
include big data processing, Internet of
things, and cloud computing. He is the director of “Big Data
Intelligent Processing Innovation Team of Huangdao District”,
director of “Smart City Research Center of Fuwode Electronic
Corp.”, and founding director of the Autonomous Service
Systems Lab. He was a research associate professor/senior
researcher at Computer Science Department, University of
Aarhus, where he had been working on the EU FP6 Hydra
pervasive middleware project, for which he was a technical
manager (Aug. 2008–Dec. 2009). He was a visiting scholar
of Department of Systems and Computer Engineering, Carleton
University, Canada (Jan. 2006–Jan. 2007). He was an associate
professor at School of Software Engineering, Tongji University,
Shanghai, China (Aug. 2003–June 2007). He was a NSTB post-
doctoral research fellow at Department of Computer Science,
National University of Singapore (Sept. 2001 to Aug. 2003). His
current h-index according to google scholar is 13 and the number
of total citations is around 530 in Sept. 2015.
Yong Wang is a master student working
on modeling and validation for cloud
environment using colored Petri net. He
graduated from Nanjing University of
Chinese Medicine with his bachelor degree
in 2012.
Xiwei Xu is a researcher in the Software
Systems Research Group at NICTA.
Her research interests include software
architecture, dependable distributed
systems, service/cloud engineering
especially RESTful services, and business
process management and she is currently
involved in the Dependable Cloud
Computing Project and the Security Architecture Project. She
got her bachelor degree from Nankai University in 2007 and
PhD degree from The Univeristy of New South Wales in 2012.
She has been in an 7-month internship experience in Aragon
Consulting Group (Nov. 2006–May 2007) focusing on web 2.0
development/AJAX.
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