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Parallel and Distributed System IEEE 2015 Projects
Web : www.kasanpro.com Email : sales@kasanpro.com
List Link : http://kasanpro.com/projects-list/parallel-and-distributed-system-ieee-2015-projects
Title :Human Mobility Enhances Global Positioning Accuracy for Mobile Phone Localization
Language : C#
Project Link : http://kasanpro.com/p/c-sharp/mobile-phone-localization-withs-global-positioning-accuracy
Abstract : Global Positioning System (GPS) has enabled a number of geographical applications over many years.
Quite a lot of location-based services, however, still suffer from considerable positioning errors of GPS (usually 1m to
20m in practice). In this study, we design and implement a high-accuracy global positioning solution based on GPS
and human mobility captured by mobile phones. Our key observation is that smartphone-enabled dead reckoning
supports accurate but local coordinates of users' trajectories, while GPS provides global but inconsistent coordinates.
Considering them simultaneously, we devise techniques to refine the global positioning results by fitting the global
positions to the structure of locally measured ones, so the refined positioning results are more likely to elicit the
ground truth. We develop a prototype system, named GloCal, and conduct comprehensive experiments in both
crowded urban and spacious suburban areas. The evaluation results show that GloCal can achieve 30%
improvement on average error with respect to GPS. GloCal uses merely mobile phones and requires no infrastructure
or additional reference information. As an effective and light-weight augmentation to global positioning, GloCal holds
promise in real-world feasibility.
Title :Distributed Smart-home Decision-making in a Hierarchical Interactive Smart Grid Architecture
Language : C#
Project Link : http://kasanpro.com/p/c-sharp/distributed-smart-home-decision-making-smart-grid-architecture
Abstract : In this paper, we develop a comprehensive real-time interactive framework for the Utility and customers in
a smart grid while ensuring grid-stability and Quality-of-Service (QoS). First, we propose a hierarchical architecture for
the Utility-customer interaction consisting of sub-components of customer load prediction, renewable generation
integration, power-load balancing and demand response (DR). Within this hierarchical architecture, we focus on the
problem of real-time scheduling in an abstract grid model consisting of one controller and multiple customer units. A
scalable solution to the real-time scheduling problem is proposed by combining solutions to two sub-problems: (1)
centralized sequential decision making at the controller to maximize an accumulated reward for the whole micro-grid
and (2) distributed auctioning among all customers based on the optimal load profile obtained by solving the first
problem to coordinate their interactions. We formulate the centralized sequential decision making at the controller as
a hidden mode Markov decision process (HM-MDP). Next, a Vikrey auctioning game is designed to coordinate the
actions of the individual smart-homes to actually achieve the optimal solution derived by the controller under realistic
gird interaction assumptions. We show that though truthful bidding is a weakly dominant strategy for all smart-homes
in the auctioning game, collusive equilibria do exist and can jeopardize the effectiveness and efficiency of the trading
opportunity allocation. Analysis on the structure of the Bayesian Nash equilibrium solution set shows that the Vickrey
auctioning game can be made more robust against collusion by customers (anticipating distributed smart-homes) by
introducing a positive reserve price. The corresponding auctioning game is then shown to converge to the unique
incentive compatible truthful bidding Bayesian Nash equilibrium, without jeopardizing the auctioneer's (microgrid
controller's) profit. The paper also explicitly discusses how this two- step solution approach can be scaled to be
suitable for more complicated smart grid architectures beyond the assumed abstract model.
Title :Shared Authority Based Privacy-preserving Authentication Protocol in Cloud Computing
Language : NS2
Project Link : http://kasanpro.com/p/ns2/privacy-preserving-authentication-protocol-shared-authority-cloud
Abstract : Cloud computing is emerging as a prevalent data interactive paradigm to realize users' data remotely
stored in an online cloud server. Cloud services provide great conveniences for the users to enjoy the on-demand
cloud applications without considering the local infrastructure limitations. During the data accessing, different users
may be in a collaborative relationship, and thus data sharing becomes significant to achieve productive benefits. The
existing security solutions mainly focus on the authentication to realize that a user's privative data cannot be
unauthorized accessed, but neglect a subtle privacy issue during a user challenging the cloud server to request other
users for data sharing. The challenged access request itself may reveal the user's privacy no matter whether or not it
can obtain the data access permissions. In this paper, we propose a shared authority based privacy-preserving
authentication protocol (SAPA) to address above privacy issue for cloud storage. In the SAPA, 1) shared access
authority is achieved by anonymous access request matching mechanism with security and privacy considerations
(e.g., authentication, data anonymity, user privacy, and forward security); 2) attribute based access control is adopted
to realize that the user can only access its own data fields; 3) proxy re-encryption is applied by the cloud server to
provide data sharing among the multiple users. Meanwhile, universal composability (UC) model is established to
prove that the SAPA theoretically has the design correctness. It indicates that the proposed protocol realizing
privacy-preserving data access authority sharing, is attractive for multi-user collaborative cloud applications.
Title :Shared Authority Based Privacy-preserving Authentication Protocol in Cloud Computing
Language : C#
Project Link :
http://kasanpro.com/p/c-sharp/shared-authority-based-privacy-preserving-authentication-protocol-cloud-computing
Abstract : Cloud computing is emerging as a prevalent data interactive paradigm to realize users' data remotely
stored in an online cloud server. Cloud services provide great conveniences for the users to enjoy the on-demand
cloud applications without considering the local infrastructure limitations. During the data accessing, different users
may be in a collaborative relationship, and thus data sharing becomes significant to achieve productive benefits. The
existing security solutions mainly focus on the authentication to realize that a user's privative data cannot be
unauthorized accessed, but neglect a subtle privacy issue during a user challenging the cloud server to request other
users for data sharing. The challenged access request itself may reveal the user's privacy no matter whether or not it
can obtain the data access permissions. In this paper, we propose a shared authority based privacy-preserving
authentication protocol (SAPA) to address above privacy issue for cloud storage. In the SAPA, 1) shared access
authority is achieved by anonymous access request matching mechanism with security and privacy considerations
(e.g., authentication, data anonymity, user privacy, and forward security); 2) attribute based access control is adopted
to realize that the user can only access its own data fields; 3) proxy re-encryption is applied by the cloud server to
provide data sharing among the multiple users. Meanwhile, universal composability (UC) model is established to
prove that the SAPA theoretically has the design correctness. It indicates that the proposed protocol realizing
privacy-preserving data access authority sharing, is attractive for multi-user collaborative cloud applications.
Title :Efficient and Cost-Effective Hybrid Congestion Control for HPC Interconnection Networks
Language : NS2
Project Link : http://kasanpro.com/p/ns2/efficient-cost-effective-hybrid-congestion-control
Abstract : Interconnection networks are key components in high-performance computing (HPC) systems, their
performance having a strong influence on the overall system one. However, at high load, congestion and its negative
effects (e.g., Head-of-line blocking) threaten the performance of the network, and so the one of the entire system.
Congestion control (CC) is crucial to ensure an efficient utilization of the interconnection network during congestion
situations. As one major trend is to reduce the effective wiring in interconnection networks to reduce cost and power
consumption, the network will operate very close to its capacity. Thus, congestion control becomes essential. Existing
CC techniques can be divided into two general approaches. One is to throttle traffic injection at the sources that
contribute to congestion, and the other is to isolate the congested traffic in specially designated resources. However,
both approaches have different, but non-overlapping weaknesses: injection throttling techniques have a slow reaction
against congestion, while isolating traffic in special resources may lead the system to run out of those resources. In
this paper we propose EcoCC, a new Efficient and Cost-Effective CC technique, that combines injection throttling and
congested-flow isolation to minimize their respective drawbacks and maximize overall system performance. This new
strategy is suitable for current commercial switch architectures, where it could be implemented without requiring
significant complexity. Experimental results, using simulations under synthetic and real trace-based traffic patterns,
show that this technique improves by up to 55 percent over some of the most successful congestion control
techniques.
Parallel and Distributed System IEEE 2015 Projects
Title :Efficient and Cost-Effective Hybrid Congestion Control for HPC Interconnection Networks
Language : C#
Project Link :
http://kasanpro.com/p/c-sharp/efficient-cost-effective-hybrid-congestion-control-hpc-interconnection-networks
Abstract : Interconnection networks are key components in high-performance computing (HPC) systems, their
performance having a strong influence on the overall system one. However, at high load, congestion and its negative
effects (e.g., Head-of-line blocking) threaten the performance of the network, and so the one of the entire system.
Congestion control (CC) is crucial to ensure an efficient utilization of the interconnection network during congestion
situations. As one major trend is to reduce the effective wiring in interconnection networks to reduce cost and power
consumption, the network will operate very close to its capacity. Thus, congestion control becomes essential. Existing
CC techniques can be divided into two general approaches. One is to throttle traffic injection at the sources that
contribute to congestion, and the other is to isolate the congested traffic in specially designated resources. However,
both approaches have different, but non-overlapping weaknesses: injection throttling techniques have a slow reaction
against congestion, while isolating traffic in special resources may lead the system to run out of those resources. In
this paper we propose EcoCC, a new Efficient and Cost-Effective CC technique, that combines injection throttling and
congested-flow isolation to minimize their respective drawbacks and maximize overall system performance. This new
strategy is suitable for current commercial switch architectures, where it could be implemented without requiring
significant complexity. Experimental results, using simulations under synthetic and real trace-based traffic patterns,
show that this technique improves by up to 55 percent over some of the most successful congestion control
techniques.

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Parallel and Distributed System IEEE 2015 Projects

  • 1. Parallel and Distributed System IEEE 2015 Projects Web : www.kasanpro.com Email : sales@kasanpro.com List Link : http://kasanpro.com/projects-list/parallel-and-distributed-system-ieee-2015-projects Title :Human Mobility Enhances Global Positioning Accuracy for Mobile Phone Localization Language : C# Project Link : http://kasanpro.com/p/c-sharp/mobile-phone-localization-withs-global-positioning-accuracy Abstract : Global Positioning System (GPS) has enabled a number of geographical applications over many years. Quite a lot of location-based services, however, still suffer from considerable positioning errors of GPS (usually 1m to 20m in practice). In this study, we design and implement a high-accuracy global positioning solution based on GPS and human mobility captured by mobile phones. Our key observation is that smartphone-enabled dead reckoning supports accurate but local coordinates of users' trajectories, while GPS provides global but inconsistent coordinates. Considering them simultaneously, we devise techniques to refine the global positioning results by fitting the global positions to the structure of locally measured ones, so the refined positioning results are more likely to elicit the ground truth. We develop a prototype system, named GloCal, and conduct comprehensive experiments in both crowded urban and spacious suburban areas. The evaluation results show that GloCal can achieve 30% improvement on average error with respect to GPS. GloCal uses merely mobile phones and requires no infrastructure or additional reference information. As an effective and light-weight augmentation to global positioning, GloCal holds promise in real-world feasibility. Title :Distributed Smart-home Decision-making in a Hierarchical Interactive Smart Grid Architecture Language : C# Project Link : http://kasanpro.com/p/c-sharp/distributed-smart-home-decision-making-smart-grid-architecture Abstract : In this paper, we develop a comprehensive real-time interactive framework for the Utility and customers in a smart grid while ensuring grid-stability and Quality-of-Service (QoS). First, we propose a hierarchical architecture for the Utility-customer interaction consisting of sub-components of customer load prediction, renewable generation integration, power-load balancing and demand response (DR). Within this hierarchical architecture, we focus on the problem of real-time scheduling in an abstract grid model consisting of one controller and multiple customer units. A scalable solution to the real-time scheduling problem is proposed by combining solutions to two sub-problems: (1) centralized sequential decision making at the controller to maximize an accumulated reward for the whole micro-grid and (2) distributed auctioning among all customers based on the optimal load profile obtained by solving the first problem to coordinate their interactions. We formulate the centralized sequential decision making at the controller as a hidden mode Markov decision process (HM-MDP). Next, a Vikrey auctioning game is designed to coordinate the actions of the individual smart-homes to actually achieve the optimal solution derived by the controller under realistic gird interaction assumptions. We show that though truthful bidding is a weakly dominant strategy for all smart-homes in the auctioning game, collusive equilibria do exist and can jeopardize the effectiveness and efficiency of the trading opportunity allocation. Analysis on the structure of the Bayesian Nash equilibrium solution set shows that the Vickrey auctioning game can be made more robust against collusion by customers (anticipating distributed smart-homes) by introducing a positive reserve price. The corresponding auctioning game is then shown to converge to the unique incentive compatible truthful bidding Bayesian Nash equilibrium, without jeopardizing the auctioneer's (microgrid controller's) profit. The paper also explicitly discusses how this two- step solution approach can be scaled to be suitable for more complicated smart grid architectures beyond the assumed abstract model. Title :Shared Authority Based Privacy-preserving Authentication Protocol in Cloud Computing Language : NS2 Project Link : http://kasanpro.com/p/ns2/privacy-preserving-authentication-protocol-shared-authority-cloud Abstract : Cloud computing is emerging as a prevalent data interactive paradigm to realize users' data remotely stored in an online cloud server. Cloud services provide great conveniences for the users to enjoy the on-demand cloud applications without considering the local infrastructure limitations. During the data accessing, different users may be in a collaborative relationship, and thus data sharing becomes significant to achieve productive benefits. The
  • 2. existing security solutions mainly focus on the authentication to realize that a user's privative data cannot be unauthorized accessed, but neglect a subtle privacy issue during a user challenging the cloud server to request other users for data sharing. The challenged access request itself may reveal the user's privacy no matter whether or not it can obtain the data access permissions. In this paper, we propose a shared authority based privacy-preserving authentication protocol (SAPA) to address above privacy issue for cloud storage. In the SAPA, 1) shared access authority is achieved by anonymous access request matching mechanism with security and privacy considerations (e.g., authentication, data anonymity, user privacy, and forward security); 2) attribute based access control is adopted to realize that the user can only access its own data fields; 3) proxy re-encryption is applied by the cloud server to provide data sharing among the multiple users. Meanwhile, universal composability (UC) model is established to prove that the SAPA theoretically has the design correctness. It indicates that the proposed protocol realizing privacy-preserving data access authority sharing, is attractive for multi-user collaborative cloud applications. Title :Shared Authority Based Privacy-preserving Authentication Protocol in Cloud Computing Language : C# Project Link : http://kasanpro.com/p/c-sharp/shared-authority-based-privacy-preserving-authentication-protocol-cloud-computing Abstract : Cloud computing is emerging as a prevalent data interactive paradigm to realize users' data remotely stored in an online cloud server. Cloud services provide great conveniences for the users to enjoy the on-demand cloud applications without considering the local infrastructure limitations. During the data accessing, different users may be in a collaborative relationship, and thus data sharing becomes significant to achieve productive benefits. The existing security solutions mainly focus on the authentication to realize that a user's privative data cannot be unauthorized accessed, but neglect a subtle privacy issue during a user challenging the cloud server to request other users for data sharing. The challenged access request itself may reveal the user's privacy no matter whether or not it can obtain the data access permissions. In this paper, we propose a shared authority based privacy-preserving authentication protocol (SAPA) to address above privacy issue for cloud storage. In the SAPA, 1) shared access authority is achieved by anonymous access request matching mechanism with security and privacy considerations (e.g., authentication, data anonymity, user privacy, and forward security); 2) attribute based access control is adopted to realize that the user can only access its own data fields; 3) proxy re-encryption is applied by the cloud server to provide data sharing among the multiple users. Meanwhile, universal composability (UC) model is established to prove that the SAPA theoretically has the design correctness. It indicates that the proposed protocol realizing privacy-preserving data access authority sharing, is attractive for multi-user collaborative cloud applications. Title :Efficient and Cost-Effective Hybrid Congestion Control for HPC Interconnection Networks Language : NS2 Project Link : http://kasanpro.com/p/ns2/efficient-cost-effective-hybrid-congestion-control Abstract : Interconnection networks are key components in high-performance computing (HPC) systems, their performance having a strong influence on the overall system one. However, at high load, congestion and its negative effects (e.g., Head-of-line blocking) threaten the performance of the network, and so the one of the entire system. Congestion control (CC) is crucial to ensure an efficient utilization of the interconnection network during congestion situations. As one major trend is to reduce the effective wiring in interconnection networks to reduce cost and power consumption, the network will operate very close to its capacity. Thus, congestion control becomes essential. Existing CC techniques can be divided into two general approaches. One is to throttle traffic injection at the sources that contribute to congestion, and the other is to isolate the congested traffic in specially designated resources. However, both approaches have different, but non-overlapping weaknesses: injection throttling techniques have a slow reaction against congestion, while isolating traffic in special resources may lead the system to run out of those resources. In this paper we propose EcoCC, a new Efficient and Cost-Effective CC technique, that combines injection throttling and congested-flow isolation to minimize their respective drawbacks and maximize overall system performance. This new strategy is suitable for current commercial switch architectures, where it could be implemented without requiring significant complexity. Experimental results, using simulations under synthetic and real trace-based traffic patterns, show that this technique improves by up to 55 percent over some of the most successful congestion control techniques. Parallel and Distributed System IEEE 2015 Projects Title :Efficient and Cost-Effective Hybrid Congestion Control for HPC Interconnection Networks Language : C# Project Link : http://kasanpro.com/p/c-sharp/efficient-cost-effective-hybrid-congestion-control-hpc-interconnection-networks Abstract : Interconnection networks are key components in high-performance computing (HPC) systems, their
  • 3. performance having a strong influence on the overall system one. However, at high load, congestion and its negative effects (e.g., Head-of-line blocking) threaten the performance of the network, and so the one of the entire system. Congestion control (CC) is crucial to ensure an efficient utilization of the interconnection network during congestion situations. As one major trend is to reduce the effective wiring in interconnection networks to reduce cost and power consumption, the network will operate very close to its capacity. Thus, congestion control becomes essential. Existing CC techniques can be divided into two general approaches. One is to throttle traffic injection at the sources that contribute to congestion, and the other is to isolate the congested traffic in specially designated resources. However, both approaches have different, but non-overlapping weaknesses: injection throttling techniques have a slow reaction against congestion, while isolating traffic in special resources may lead the system to run out of those resources. In this paper we propose EcoCC, a new Efficient and Cost-Effective CC technique, that combines injection throttling and congested-flow isolation to minimize their respective drawbacks and maximize overall system performance. This new strategy is suitable for current commercial switch architectures, where it could be implemented without requiring significant complexity. Experimental results, using simulations under synthetic and real trace-based traffic patterns, show that this technique improves by up to 55 percent over some of the most successful congestion control techniques.