• Title/Summary/Keyword: Partition computing

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Static Timing Analysis Tool for ARM-based Embedded Software (ARM용 내장형 소프트웨어의 정적인 수행시간 분석 도구)

  • Hwang Yo-Seop;Ahn Seong-Yong;Shim Jea-Hong;Lee Jeong-A
    • Journal of KIISE:Computing Practices and Letters
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    • v.11 no.1
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    • pp.15-25
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    • 2005
  • Embedded systems have a set of tasks to execute. These tasks can be implemented either on application specific hardware or as software running on a specific processor. The design of an embedded system involves the selection of hardware software resources, Partition of tasks into hardware and software, and performance evaluation. An accurate estimation of execution time for extreme cases (best and worst case) is important for hardware/software codesign. A tighter estimation of the execution time bound nay allow the use of a slower processor to execute the code and may help lower the system cost. In this paper, we consider an ARM-based embedded system and developed a tool to estimate the tight boundary of execution time of a task with loop bounds and any additional program path information. The tool we developed is based on an exiting timing analysis tool named 'Cinderella' which currently supports i960 and m68k architectures. We add a module to handle ARM ELF object file, which extracts control flow and debugging information, and a module to handle ARM instruction set so that the new tool can support ARM processor. We validate the tool by comparing the estimated bound of execution time with the run-time execution time measured by ARMulator for a selected bechmark programs.

An Energy Estimation-based Routing Protocol for Maximizing Network Lifetime in Wireless Sensor Networks (무선 센서네트워크에서 네트워크 수명을 최대화하기 위한 에너지 추정 기반의 라우팅 프로토콜)

  • Hong, Ran-Kyung;Kweon, Ki-Suk;Ghim, Ho-Jin;Yoon, Hyun-Soo
    • Journal of KIISE:Computing Practices and Letters
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    • v.14 no.3
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    • pp.281-285
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    • 2008
  • Wireless sensor networks are closely related with the geometric environment in which they are deployed. We consider the probable case when a routing protocol runs on an environment with many complex obstacles like downtown surroundings. In addition, there are no unrealistic assumptions in order to increase practicality of the protocol. Our goal is to find a routing protocol for maximizing network lifetime by using only connectivity information in the complex sensor network environment. We propose a topology-based routing algorithm that accomplishes good performance in terms of network lifetime and routing complexity as measures. Our routing algorithm makes routing decision based on a weighted graph as topological abstraction of the complex network. The graph conduces to lifetime enhancement by giving alternative paths, distributing the skewed burden. An energy estimation method is used so as to maintain routing information without any additional cost. We show how our approach can be used to maximize network lifetime and by extensive simulation we prove that out approach gives good results in terms of both measures-network lifetime and routing complexity.

On Generating Backbone Based on Energy and Connectivity for WSNs (무선 센서네트워크에서 노드의 에너지와 연결성을 고려한 클러스터 기반의 백본 생성 알고리즘)

  • Shin, In-Young;Kim, Moon-Seong;Choo, Hyun-Seung
    • Journal of Internet Computing and Services
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    • v.10 no.5
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    • pp.41-47
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    • 2009
  • Routing through a backbone, which is responsible for performing and managing multipoint communication, reduces the communication overhead and overall energy consumption in wireless sensor networks. However, the backbone nodes will need extra functionality and therefore consume more energy compared to the other nodes. The power consumption imbalance among sensor nodes may cause a network partition and failures where the transmission from some sensors to the sink node could be blocked. Hence optimal construction of the backbone is one of the pivotal problems in sensor network applications and can drastically affect the network's communication energy dissipation. In this paper a distributed algorithm is proposed to generate backbone trees through robust multi-hop clusters in wireless sensor networks. The main objective is to form a properly designed backbone through multi-hop clusters by considering energy level and degree of each node. Our improved cluster head selection method ensures that energy is consumed evenly among the nodes in the network, thereby increasing the network lifetime. Comprehensive computer simulations have indicated that the newly proposed scheme gives approximately 10.36% and 24.05% improvements in the performances related to the residual energy level and the degree of the cluster heads respectively and also prolongs the network lifetime.

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An Energy-Efficient Clustering Using Division of Cluster in Wireless Sensor Network (무선 센서 네트워크에서 클러스터의 분할을 이용한 에너지 효율적 클러스터링)

  • Kim, Jong-Ki;Kim, Yoeng-Won
    • Journal of Internet Computing and Services
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    • v.9 no.4
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    • pp.43-50
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    • 2008
  • Various studies are being conducted to achieve efficient routing and reduce energy consumption in wireless sensor networks where energy replacement is difficult. Among routing mechanisms, the clustering technique has been known to be most efficient. The clustering technique consists of the elements of cluster construction and data transmission. The elements that construct a cluster are repeated in regular intervals in order to equalize energy consumption among sensor nodes in the cluster. The algorithms for selecting a cluster head node and arranging cluster member nodes optimized for the cluster head node are complex and requires high energy consumption. Furthermore, energy consumption for the data transmission elements is proportional to $d^2$ and $d^4$ around the crossover region. This paper proposes a means of reducing energy consumption by increasing the efficiency of the cluster construction elements that are regularly repeated in the cluster technique. The proposed approach maintains the number of sensor nodes in a cluster at a constant level by equally partitioning the region where nodes with density considerations will be allocated in cluster construction, and reduces energy consumption by selecting head nodes near the center of the cluster. It was confirmed through simulation experiments that the proposed approach consumes less energy than the LEACH algorithm.

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