The popularity of mobile cloud computing has provisioned a new paradigm for mobile devices to offload their computation to remote mobile cloud data center for task execution. However, the mobile cloud data center may ...
详细信息
ISBN:
(纸本)9781509018932
The popularity of mobile cloud computing has provisioned a new paradigm for mobile devices to offload their computation to remote mobile cloud data center for task execution. However, the mobile cloud data center may suffer from dramatic energy consumption. To solve this problem, we propose to migrate the workload from remote cloud data center to nearby cloudlets, so as to relieve the pressure of cloud data center and save the energy consumption. Specifically, we propose a lightweight and decentralized algorithm based on the Alternating Direction Method of Multipliers (ADMM) algorithm to construct the migration scheme. Simulations show that our algorithm can fast converge in tens of iterations, and decrease the overall energy consumption.
In this paper we present two new decentralized algorithms for autonomous intersection management and compare the performance of the algorithms with an established centralized solution. One of the algorithms addresses ...
详细信息
ISBN:
(纸本)9781509003006
In this paper we present two new decentralized algorithms for autonomous intersection management and compare the performance of the algorithms with an established centralized solution. One of the algorithms addresses the problem through an unstructured peer-to-peer approach and the other uses a Distributed Hash Table to distribute knowledge of intersection usage among participating vehicles. We evaluate these algorithms through simulation and by comparing average delay to the performance of a centralized reservation-based algorithm. We find that in times of light congestion the decentralized algorithms perform as well as the centralized approach. During times of moderate or heavy congestion the unstructured peer-to-peer algorithm performs better than the centralized algorithm, and the DHT-based algorithm performs worse.
Dynamic spectrum sharing can improve the efficiency of spectrum utilization. Spectrum trading between primary users (PUs) and secondary users (SUs) is a popular and efficient way to fulfill this kind of spectrum shari...
详细信息
ISBN:
(纸本)9783319218373;9783319218366
Dynamic spectrum sharing can improve the efficiency of spectrum utilization. Spectrum trading between primary users (PUs) and secondary users (SUs) is a popular and efficient way to fulfill this kind of spectrum sharing. In this paper we present a novel spectrum trading mechanism which operate among secondary users. More specifically, some secondary users which has leased spectrum from PUs can sublet it to other SUs to reduce their own leasing cost. Then all of the SUs can share these spectrum bands to conduct data transmission respectively. This leads to a new multi-leader multi-follower (MLMF) game which is different from existing works. The existence of Nash equilibrium of this formulated game is proven by redefining it as a shared MLMF constraint game. A decentralized algorithm is then proposed to find Nash equilibrium of this two tiers game with only local information. Simulations are provided to illustrate the convergence and effectiveness of the proposed algorithm.
A distributed doubly linked list (or bidirectional ring) is a fundamental distributed data structure commonly used in structured peer-to-peer networks. This paper presents DDLL, a novel decentralized algorithm for con...
详细信息
ISBN:
(纸本)9781509003006
A distributed doubly linked list (or bidirectional ring) is a fundamental distributed data structure commonly used in structured peer-to-peer networks. This paper presents DDLL, a novel decentralized algorithm for constructing distributed doubly linked lists. In the absence of failure, DDLL maintains consistency with regard to lookups of nodes, even while multiple nodes are simultaneously being inserted or deleted. Unlike existing algorithms, DDLL adopts a novel strategy based on conflict detection and sequence numbers. A formal description and correctness proofs are given. Simulation results show that DDLL outperforms conventional algorithms in terms of both time and number of messages.
When using multiple robotic agents for waypoint-based exploration or coverage tasks, collision avoidance between agents is an important issue. With a centralized planner, this issue arises only at one central instance...
详细信息
ISBN:
(纸本)9781479977871
When using multiple robotic agents for waypoint-based exploration or coverage tasks, collision avoidance between agents is an important issue. With a centralized planner, this issue arises only at one central instance. However, when using asynchronous and/or decentralized algorithms, decentralized methods for collision avoidance need to be used. We propose a novel approach based on the asynchronous backtracking (ABT) algorithm which provides decentralized constraint satisfaction called continuous ABT(C-ABT). C-ABT is a continuous extension to ABT intended as a collision avoidance layer for existing multi-agent waypoint navigation. It extends ABT in the sense that participating agents know when they found a valid solution. In this case, agents can safely move to their selected waypoints. While ABT only finds one static solution, C-ABT is suited for continuously providing new waypoints for all agents. By using the concept of local neighborhoods, C-ABT is also scalable to swarms of arbitrary size.
In this paper, we investigate a decentralized approach to timestamping transactions in a replicated database, under partial replication in Peer-To-Peer (P2P) environments. In order to solve problems of concurrent upda...
详细信息
The popularity of mobile cloud computing has provisioned a new paradigm for mobile devices to offload their computation to remote mobile cloud data center for task execution. However, the mobile cloud data center may ...
详细信息
ISBN:
(纸本)9781509018949
The popularity of mobile cloud computing has provisioned a new paradigm for mobile devices to offload their computation to remote mobile cloud data center for task execution. However, the mobile cloud data center may suffer from dramatic energy consumption. To solve this problem, we propose to migrate the workload from remote cloud data center to nearby cloudlets, so as to relieve the pressure of cloud data center and save the energy consumption. Specifically, we propose a light-weight and decentralized algorithm based on the Alternating Direction Method of Multipliers (ADMM) algorithm to construct the migration scheme. Simulations show that our algorithm can fast converge in tens of iterations, and decrease the overall energy consumption.
In a vehicle-to-grid (V2G) system, aggregators coordinate the charging/discharging schedules of electric vehicle (EV) batteries so that they can collectively form a massive energy storage system to provide ancillary s...
详细信息
In a vehicle-to-grid (V2G) system, aggregators coordinate the charging/discharging schedules of electric vehicle (EV) batteries so that they can collectively form a massive energy storage system to provide ancillary services, such as frequency regulation, to the power grid. In this paper, the optimal charging/discharging scheduling between one aggregator and its coordinated EVs for the provision of the regulation service is studied. We propose a scheduling method that assures adequate charging of EVs and the quality of the regulation service at the same time. First, the scheduling problem is formulated as a convex optimization problem relying on accurate forecasts of the regulation demand. By exploiting the zero-energy nature of the regulation service, the forecast-based scheduling in turn degenerates to an online scheduling problem to cope with the high uncertainty in the forecasts. decentralized algorithms based on the gradient projection method are designed to solve the optimization problems, enabling each EV to solve its local problem and to obtain its own schedule. Our simulation study of 1000 EVs shows that the proposed online scheduling can perform nearly as well as the forecast-based scheduling, and it is able to smooth out the real-time power fluctuations of the grid, demonstrating the potential of V2G in providing the regulation service.
This paper proposes a novel base station (BS) coordination approach for intercell interference mitigation in the orthogonal frequency-division multiple access based cellular networks. Specifically, we first propose a ...
详细信息
This paper proposes a novel base station (BS) coordination approach for intercell interference mitigation in the orthogonal frequency-division multiple access based cellular networks. Specifically, we first propose a new performance metric for evaluating end user's quality of experience (QoE), which jointly considers spectrum efficiency, user fairness, and service satisfaction. Interference graph is applied here to capture and analyze the interactions between BSs. Then, a QoE-oriented resource allocation problem is formulated among BSs as a local cooperation game, where BSs are encouraged to cooperate with their peer nodes in the adjacent cells in user scheduling and power allocation. The existence of the joint-strategy Nash equilibrium (NE) has been proved, in which no BS player would unilaterally change its own strategy in user scheduling or power allocation. Furthermore, the NE in the formulated game is proved to lead to the global optimality of the network utility. Accordingly, we design an iterative searching algorithm to obtain the global optimum (i.e., the best NE) with an arbitrarily high probability in a decentralized manner, in which only local information exchange is needed. Theoretical analysis and simulation results both validate the convergence and optimality of the proposed algorithm with fairness improvement.
The problem of establishing minimum-cost multicast connections in coded networks can be viewed as an optimization problem, and decentralized algorithms were proposed by Lun et al. to compute the optimal subgraph using...
详细信息
The problem of establishing minimum-cost multicast connections in coded networks can be viewed as an optimization problem, and decentralized algorithms were proposed by Lun et al. to compute the optimal subgraph using the dual subgradient method. However, the convergence rate problem for these algorithms remains open. There are limited results in the literature, which bound the amount of infeasibility of the primal solution recovered after each iterations or the convergence rate. However, due to the special structure of the network coding problem, we have an algorithm that generates a feasible solution after each iterations. In addition, the convergence rate of the primal problem is O(1/n) to a neighborhood of the optimal solution. We also propose heuristics to further improve our algorithm and demonstrate through simulations that the distributed algorithm converges to the optimal subgraph quickly and is robust against network topology changes.
暂无评论