With the advent of the 5G era, the demands for features such as low latency and high concurrency are becoming increasingly significant. These sophisticated new network applications and services require huge gaps in ne...
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With the advent of the 5G era, the demands for features such as low latency and high concurrency are becoming increasingly significant. These sophisticated new network applications and services require huge gaps in network transmission bandwidth, network transmission latency, and user experience, making cloud computing face many technical challenges in terms of applicability. In response to cloud computing's shortcomings, edge computing has come into its own. However, many factors affect task offloading and resource allocation in the edge computing environment, such as the task offload latency, energy consumption, smart device mobility, end-user power, and other issues. This paper proposes a dynamic multi-winner game model based on incomplete information to solve multi-end users' task offloading and edge resource allocation. First, based on the history of end-users storage in edge data centers, a hidden Markov model can predict other end-users' bid prices at time t. Based on these predicted auction prices, the model determines their bids. A dynamic multi-winner game model is used to solve the offload strategy that minimizes latency, energy consumption, cost, and to maximizes end-user satisfaction at the edge data center. Finally, the authors designed a resource allocation algorithm based on different priorities and task types to implement resource allocation in edge data centers. To ensure the prediction model's accuracy, the authors also use the expectationmaximization algorithm to learn the model parameters. Comparative experimental results show that the proposed model can better results in time delay, energy consumption, and cost.
QoS provisioning and high capacity for high mobility users are considered as the distresses of broadband wireless communications (BWC) and specifically the key technology of WiMAX. Hence, the scheduling and resource a...
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QoS provisioning and high capacity for high mobility users are considered as the distresses of broadband wireless communications (BWC) and specifically the key technology of WiMAX. Hence, the scheduling and resource allocation algorithms play the main role in this regard. In the research conducted on scheduling algorithms in WiMAX network, two principal methods of AMC and PUSC are used. The high capacity in AMC mode algorithms is achieved by considering the low speed users. Conversely, in PUSC mode algorithms, speed does not affect the network performances;however, the capacity is low. To date, the importance of presenting QoS and maintaining the network capacity for the users with different speeds has not been acknowledged yet. This paper presents novel scheduling algorithms and also new frame partitioning scheme which are proper for the users with different mobility speeds. The new algorithm uses two modes of AMC and PUSC simultaneously to maintain the high capacity of the network. QoS is also provided. The simulation results reveal that our algorithm increases capacity while it presents low packet delay and packet loss rate in the presence of both high and low mobility speed users.
In the recent past, security-sensitive applications, such as electronic transaction processing systems, stock quote update systems, which require high quality of security to guarantee authentication, integrity, and co...
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In the recent past, security-sensitive applications, such as electronic transaction processing systems, stock quote update systems, which require high quality of security to guarantee authentication, integrity, and confidentiality of information, have adopted heterogeneous distributed system (HDS) as their platforms. This is primarily due to the fact that single parallel-architecture-based systems may not be sufficient to exploit the available parallelism with the running applications. Most security-aware applications end up in handling dependence tasks, also referred to as Directed Acyclic Graph (DAG), on these HDSs. Unfortunately, most existing algorithms for scheduling such DAGs in HDS fail to fully consider security requirements. In this paper, we systematically design a security-driven scheduling architecture that can dynamically measure the trust level of each node in the system by using differential equations. To do so, we introduce task priority rank to estimate security overhead of such security-critical tasks. Furthermore, we propose a security-driven scheduling algorithm for DAGs which can achieve high quality of security for applications. Our rigorous performance evaluation study results clearly demonstrate that our proposed algorithm outperforms the existing scheduling algorithms in terms of minimizing the makespan, risk probability, and speedup. We also observe that the improvement obtained by our algorithm increases as the security-sensitive data of applications increases.
Although single-hop star networks based on wavelength division multiplexing (WDM) are attractive owing to their all-optical communication features, the throughput of such lightwave networks is limited due to the small...
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Although single-hop star networks based on wavelength division multiplexing (WDM) are attractive owing to their all-optical communication features, the throughput of such lightwave networks is limited due to the small number of available wavelengths. In this paper, a wavelength-reusable local lightwave network that consists of two interconnected WDM star networks is proposed. Based on this architecture, the lower bounds for the problems of minimizing the switching duration and the number of switching modes are derived. A transmission scheduling algorithm for this architecture to efficiently reuse the wavelengths is also proposed. The analytical result shows that the proposed scheduling algorithm always produces solutions close to the lower bounds. Simulation results show that given the same number of users and available wavelengths, the solutions (in terms of the average switching duration and the average number of switching matrices) obtained by the proposed scheduling algorithm on the interconnected WDM networks are better than the optimal solution on a single-star WDM network. In most cases, the performance improvement achieves 20 to 45%.
Long term evolution (LTE) is a recently evolving technology which ensures the reliable delivery of the heterogeneous traffic services with high speed data rate and lower delays through their mobile and other hand held...
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Long term evolution (LTE) is a recently evolving technology which ensures the reliable delivery of the heterogeneous traffic services with high speed data rate and lower delays through their mobile and other hand held devices. The key feature of LTE is its traffic engineering which is used for effectively managing the network resources for efficient utilization. When LTE expertise has arisen there are some prevailing problems to be taken care of i.e. load balancing and traffic scheduling. Even LTE is the debauched technology, but it is also been anguishing from these problems. In this paper, a load balancing strategy has been espoused that is based on traffic scheduling. Various Traffic scheduling algorithms are designed earlier to assign shared resources among users to optimize the performance of LTE systems in an efficient manner. The performance of three types of scheduling algorithms is compared in this paper namely first come first serve (FCFS), round robin (RR) and hybrid algorithm which is the combination of FCFS and RR in extremes conditions. The discussed scheduling algorithms performance is measured in terms of symbol error rate and signal to noise ratio.
This paper considers the off-line roadside unit (RSU) ON/OFF scheduling problem in a sparse vehicular ad hoc network (VANET). We formulate the problem as a mixed integer non-linear programming problem and propose a he...
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This paper considers the off-line roadside unit (RSU) ON/OFF scheduling problem in a sparse vehicular ad hoc network (VANET). We formulate the problem as a mixed integer non-linear programming problem and propose a heuristic scheduling algorithm called Multi-Level Greedy (MLG) algorithm to find a suboptimal approximation. In the proposed MLG algorithm, we introduce the concepts of optimal service location and suboptimal service location. Then, we obtain the ON-OFF state matrix of RSUs. Simulation results show that the MLG algorithm can significantly reduce the energy consumption of RSUs deployed and can provide a reference basis for energy efficient scheduling in VANETs.
The concept of heterogeneous wireless networks (HWNs) is based on the coexistence and interoperability of different types of radio access technologies (RATs) such as long term evolution (LTE) and wireless local area n...
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The concept of heterogeneous wireless networks (HWNs) is based on the coexistence and interoperability of different types of radio access technologies (RATs) such as long term evolution (LTE) and wireless local area network (WEAN) in a unified wireless heterogeneous platform. Guaranteeing the quality of service (QoS) is an important issue for the next generation wireless networks which are characterized by providing different types of services. To schedule different types of service in HWN, distinct scheduling algorithms have been studied intensively in the literature. Thus in our research work, we focus on a common scheduling algorithm for the HWN where the traffic streams are classified into different categories, and each category has its own set of QoS parameters such as data rate and delay. In this article, we propose a new dynamic scheduling algorithm for HWN. The proposed solution introduces a new approach in scheduling packets while maintaining performance in wireless networks. The scheduling scheme is mainly based on transmission links' condition from the media independent handover (MIH) module, type of call (handoff call prioritization) and classes of service. In order to study the performance of the proposed scheme, we use simulation analysis and compare the performance of our scheme with a competing reference scheme called NSA (new scheduling algorithm) for wireless mesh networks in order to reveal its ability to adapt to the specific service and channel conditions. Simulation results show that under large number of users, the proposed algorithm has lower packet loss and blocking calls ratio while offers allowable average packet delay. (C) 2015 Elsevier Inc. All rights reserved.
This study improves the Quality of Experience (QoE) of the multi-queue multi-server queueing system by solving the scheduling problem. The QoE is evaluated by a novel indicator named system user-perceived throughput (...
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This study improves the Quality of Experience (QoE) of the multi-queue multi-server queueing system by solving the scheduling problem. The QoE is evaluated by a novel indicator named system user-perceived throughput (SUPT). According to the property of the traffic, the stochastic optimization problem for SUPT can be transformed into utility maximization under the constraint of queue stability. We then propose a drift-plus-penalty scheduling algorithm named max modified weight (MMW) to balance delay and utility. A Nike function for queue length replaces the queue length as the weight. Furthermore, we prove the stability of the queues based on the Foster-Lyapunov theorem and analyze the delay boundary under the proposed MMW scheduling algorithm. Finally, compared with several classical scheduling policies, the effectiveness of the MMW is verified by evaluating the average system throughput, SUPT, the average system backlog, and user-perceived throughput of the queues in three different scenarios. The simulation results show MMW policy achieves more efficient trade-off between SUPT and system delay, and is capable of maintaining system stability as max weight regardless of the system load.
Wireless sensor network (WSN) is the new invention applied for detecting the damage of the high-rise building structural health. The research has been focused in the early age and curing phase period. The objective of...
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Wireless sensor network (WSN) is the new invention applied for detecting the damage of the high-rise building structural health. The research has been focused in the early age and curing phase period. The objective of this article is to provide a solution to find out the optimum throughput, queue loss and queue size mechanism technique for tree topology sensor network in high-rise civil building structural health. Sensor technology offers new opportunities to advance monitoring for civil large building infrastructure health and maintenance by providing relevant information regarding the condition of high-rise building structure strength at a light price compared with traditional monitoring tactics. To cover the whole patient area, sensor network topology is one of the most important issues. From all investigation result shows that, queue loss of the FQ (fair queuing) buffer mechanism with Newreno, Reno, Tahoe and Vegas based tree topology network offer optimum buffering technique when Vegas DT (drop tail), SFQ (stochastic fair queuing) delivered the same output. On the other hand, Vegas based TCP (transmission control protocol) mechanism with any scheduling algorithm provides the optimum throughput tree topology sensor network. (C) 2015 Elsevier GmbH. All rights reserved.
Information and communication technology (ICT) has a profound impact on environment because of its large amount of CO2 emissions. In the past years, the research field of "green" and low power consumption ne...
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Information and communication technology (ICT) has a profound impact on environment because of its large amount of CO2 emissions. In the past years, the research field of "green" and low power consumption networking infrastructures is of great importance for both service/network providers and equipment manufacturers. An emerging technology called Cloud computing can increase the utilization and efficiency of hardware equipment. The job scheduler is needed by a cloud datacenter to arrange resources for executing jobs. In this paper, we propose a scheduling algorithm for the cloud datacenter with a dynamic voltage frequency scaling technique. Our scheduling algorithm can efficiently increase resource utilization;hence, it can decrease the energy consumption for executing jobs. Experimental results show that our scheme can reduce more energy consumption than other schemes do. The performance of executing jobs is not sacrificed in our scheme. We provide a green energy-efficient scheduling algorithm using the DVFS technique for Cloud computing datacenters. (C) 2013 Elsevier B.V. All rights reserved.
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