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Dynamic adaptive streaming over HTTP (DASH) requires a video server to transcode each original video object to all the possible bit-rate versions, resulting in high CPU power consumption. To address this, we propose a new scheme that balances quality-of-experience (QoE) against transcoding energy. We start by introducing the concept of transcoding gain to express QoE achieved as a result of transcoding...
The BROGO algorithm has been recently presented for Leader Election in Wireless Sensor and IoT Networks, where after finding a spanning tree of a network, each leaf will route a message through its branch to the root in order to determine the leader in that branch. The root will then elect the global leader among the received branch leaders. The main drawback of this algorithm is a possible failure...
Energy consumption is one of the key issues in real-time system scheduling. In this paper, a new low power algorithm (LPABOBF) is proposed for the periodic task model of real-time systems. The algorithm uses dynamic voltage scaling (DVS) to calculate the optimal static speed at the offline stage, and updates the processor speed at running time by using the slack time of both high priority tasks and...
The energy management is one of the most important issues for the efficiency and performance of the hybrid vehicular power system, including the Lithium-ion battery and Ultra-Capacitor. This paper deals with a dynamic programming based optimal control strategy proposed for the hybrid vehicular power system. The proposed method utilizes the capability of dynamic programming to treat the global optimization...
How to reduce the energy consumption of urban rail transit system is always the focus of attention. The automatic train operation(ATO) system operates trains between successive stations by controlling the speed automatically, which is very important for the train energy saving operation. The traditional ATO recommended speed curve optimization research is based on line information, train information...
Many of the existing Leader Election algorithms don't deal with energy consumption and fault tolerance since they are not mainly dedicated to autonomous systems like wireless sensor and IoT networks. It is possible to use the classical Minimum Finding (MinFind) algorithm, where each node sends its value in a broadcast mode each time a better value is received. This process is very energy consuming...
Big data workflows comprised of moldable parallel MapReduce programs running on a large number of processors have become a main consumer of energy at data centers. The degree of parallelism of each moldable job in such workflows has a significant impact on the energy efficiency of parallel computing systems, which remains largely unexplored. In this paper, we validate with experimental results the...
The massive demand of mobile data traffic stimulates the emergence of cache-enabled heterogeneous cellular networks (HetNets). Caching at the network edge can reduce the duplicated transmissions of the contents and improve users' quality of service (QoS), however, the dense deployment of cache-enabled small base stations (SBSs) and relays poses a challenge on energy consumption. Several emerging technologies...
In this paper, we develop an access controller management model which provides new opportunities for further reducing the computation repetition and data transmission redundancy for Mobile Edge Computing (MEC) in 5G network. We propose novel algorithms for solving the offloading problem with consideration of tradeoff between energy consumption and the amount of offloaded data under constraint of overall...
Nowadays, one of the most challenging design issues of battery-driven real-time embedded systems is how to reduce energy consumption such that the battery life can be prolonged. Based on dynamic voltage scaling technology, many energy-efficient real-time task scheduling algorithms have been proposed, however, relatively little work is done in the presence of task synchronization. In this paper, energy-efficient...
The energy consumption of data centers has been increasing continuously during the last years due to the rising demands of computational power especially in current Grid- and Cloud Computing systems, which directly influence the increment in operational costs as well as carbon dioxide (CO2) emission. To reduce energy consumption within the cloud data center, it required energy-aware virtual machines...
Because of the limited energies of sensors, efficient data gathering in wireless sensor network has been received a great deal of attention recently. To prolong the network lifetime, in this paper, we study the problem of scheduling a mobile sink to some specific nodes, termed anchor nodes in this paper, for data collection and reducing the energy consumption of data transmission. While considering...
In wireless sensor networks(WSNs), energy-efficiency and packet time delay are two major considerations in the design of medium access control(MAC) or routing algorithms. However, these two metrics always can't be satisfied at the same time, and existing works do not trade offthem well. In this paper, we first exploit a prediction model to evaluate the amount of packet in the next period. Then we...
The load-balanced clustering is a most significant problem for WSNs with unequal load of the sensor nodes but it is known to be an NP-hard problem. This paper introduces a new model for the problem in which the objective function is to maximize the overall minimum lifetime of the cluster heads. To solve this model, we propose a novel estimation of distribution algorithm based dynamic clustering approach...
The energy consumption of the base station(BS) accounts for great proportion of the total energy consumption of the wireless access network(WAN). It would save a large amount of energy that operators switch off a part of spare BSs during the time of less network request. It is difficult to deploy a BS energy saving strategy in the current network architecture because of the tightly coupled network...
Conventional planning and optimization of cellular networks for supporting the peak-time user demand leads to substantial wastage of electrical energy. Therefore, we propose an energy-aware dynamic network provisioning framework for realizing green mobile cellular systems by reducing energy consumption in access networks. Proposed mechanism allows base stations (BSs) to offload their entire traffic...
As a new computing paradigm, cloud computing has significantly contributed to the rapid development of massive data centers. However, the corresponding energy issue becomes increasingly challenging. In this paper, we focus on the energy saving issue for virtual machine (VM) selections on an overloaded host in a cloud computing environment. We analyze the energy influencing factors during a VM migration,...
We propose a reinforcement learning algorithm, Megh, for live migration of virtual machines that simultaneously reduces the cost of energy consumption and enhances the performance. Megh learns the uncertain dynamics of workloads as-it-goes. Megh uses a dimensionality reduction scheme to projectthe combinatorially explosive state-action space to a polynomial dimensional space. These schemes enable...
Energy data, which consists of energy consumption statistics and other related data in green data centers, grows dramatically. The energy data has great value, but many attributes within it are redundant and unnecessary. Thus attribute reduction for the energy data has been conceived as a critical step. However, many existing attribute reduction algorithms are often computationally time-consuming...
In this paper, the novel shortest energy consumption Routing Spectrum Assignment (SEC-RSA) algorithm based on Distance Adaptive Modulation (DAM) is introduced. According to the distance between source and destination for a determinate lightpath the modulation pattern is modified. The energy consumption is computed for the k-shortest path, then the one with lowest energy consumption is adopted. The...
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