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The energy consumption issue in distributed computing systems has become quite critical due to environmental concerns. In response to this, many energy-aware scheduling algorithms have been developed primarily by using the dynamic voltage-frequency scaling (DVFS) capability incorporated in recent commodity processors. The majority of these algorithms(More)
BACKGROUND Multiple Sequence Alignment (MSA) has always been an active area of research in Bioinformatics. MSA is mainly focused on discovering biologically meaningful relationships among different sequences or proteins in order to investigate the underlying main characteristics/functions. This information is also used to generate phylogenetic trees. (More)
We present a new space-efficient approach, (SparseDTW), to compute the Dynamic Time Warping (DTW) distance between two time series that always yields the optimal result. This is in contrast to other known approaches which typically sacrifice optimality to attain space efficiency. The main idea behind our approach is to dynamically exploit the existence of(More)
In recent years, the issue of energy consumption in parallel and distributed computing systems has attracted a great deal of attention. In response to this, many energyaware scheduling algorithms have been developed primarily using the dynamic voltagefrequency scaling (DVFS) capability which has been incorporated into recent commodity processors. Majority(More)
This work presents a new approach to solve the location management problem by using the location areas approach. A modified genetic algorithm is used to find the optimal configuration of location areas in a mobile network. The location areas configuration of the network is modeled so that the general condition of all the chromosomes of each population(More)
In this chapter we focus on slack reclamation and propose a new slack reclamation technique, Multiple Frequency Selection DVFS (MFS-DVFS). The key idea is to execute each task with a linear combination of more than one frequency such that this combination results in using the lowest energy by covering the whole slack time of the task. We have tested our(More)
Optimizing task scheduling in a distributed heterogeneous computing environment, which is a nonlinear multi-objective NP-hard problem, plays a critical role in decreasing service response time and cost, and boosting Quality of Service (QoS). This paper, considers four conflicting objectives, namely minimizing task transfer time, task execution cost, power(More)
With popularity of data centers, energy efficiency of Ethernet switches in them is becoming a critical issue. Most existing energy saving approaches use a centralized methodology that assumes global knowledge of data center networks. Though these approaches can achieve nearly optimal energy saving for static traffic patterns, they are not suitable when the(More)
Data gathering in a timely and reliable fashion has been a key concern in wireless sensor networks particularly related to military applications. The introduction of real time communication has created additional challenges in this area with different communication constraints. Since sensor networks represent a new generation of time-critical applications,(More)