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31st Chinese Control Conference

作者： Zheng Wei Gao Shouwei Qiu Liang Zhang Weidong Shanghai Jiao Tong Univ Dept Automat Shanghai 200240 Peoples R China Shanghai Jiao Tong Univ Minist Educ China Key Lab Syst Control & Informat Proc Shanghai 200240 Peoples R China Shanghai Univ Sch Mechatron Engn & Automat Shanghai 200072 Peoples R China

ISBN: (纸本)9789881563811

Topology management is crucial to the efficiency of a wireless communication network in which all nodes are energy constraint. Clustering is a kind of energy efficient algorithm, while using a virtual backbone constructed by Connected Dominating Set (CDS) to organize the nodes is a better way. We propose an energy efficient Clustering algorithm based on Local CDS construction (CLCDS) to form the CDS-based backbone with local information exchanges. In this algorithm, each node builds its local spanning tree independently and computes its degree flag to determine whether to act as a dominating node. As we elect the dominating nodes first and then connect them by a RNG [13] based algorithm, the number of border nodes and dominating nodes obtained by our algorithm is greatly reduced compared with previous researches. The correctness of the algorithm is proven and the efficiency is compared with other clustering heuristics using simulations. As the cluster balance will have a significant impact on the network performance, we also provide with a tunable scheme to achieve a fairly balanced cluster distribution across the networks.

关键词： clustering algorithm connect domination set energy efficient algorithm graph theory

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energy efficient grid based k-means clustering algorithm for large scale wireless sensor networks

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INTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS 2022年第14期35卷 e5255-e5255页

作者： Ben Gouissem, Bechir Gantassi, Rahma Hasnaoui, Salem Univ Tunis El Manar Natl Engn Sch Tunis Commun Syst Lab SysCom BP 37 Tunis 1002 Tunisia

Hierarchical based routing is a kind of group-based routing that consists in creating of a virtual hierarchy among network sensor nodes. This class of routing technique is generally designed for large-scale networks. It aims to efficiently increase network lifetime by cutting the whole network into clusters. However, traditional clustering techniques show some limitations and do not take into consideration the self-organized with dynamic topology inherent in wireless sensor networks (WSNs). These limitations can lead to an unbalanced cluster head distribution that affects the whole network energy consumption. In this paper, we propose a grid-based k-means clustering protocol (named GBK), which combines grid-based routing with k-means algorithm in order to overcome the above mentioned weaknesses. From the supervised zone area size parameter, the base station determines the optimal grid size based on our optimization study. Afterwards, the k-means algorithm is executed in every grid cell generating a cluster head per cell grid where the nearest node to the grid cell centroid is elected. An enhancement of this proposed GBK algorithm named GBK-R is also proposed to extend network stability of the GBK algorithm by node scoring calculation that take as parameters the node remaining energy in addition to the distance to centroid. Our proposed GBK and GBK-R algorithms allow for an enhanced network stability and increase the network lifetime as demonstrated by our performance evaluation study. In addition, this GBK clustering algorithm provides a better network topology control and a better control of the random nature of node distribution by generating cluster heads with bounded localization.

关键词： clustering algorithm energy efficient algorithm grid-based algorithm k-means algorithm large scale WSN machine learning

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A CDS-Based Topology Control algorithm in energy efficient Clustering

A CDS-Based Topology Control Algorithm in Energy Efficient C...

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第三十一届中国控制会议

作者： ZHENG Wei~1,GAO Shouwei~2,QIU Liang~1,ZHANG Weidong~1 1.Department of Automation and Key Laboratory of Sy stem Control and Information Processing, Ministry of Education of China, Shanghai Jiao Tong University,Shanghai 200240,China 2.School of Mechatronics Engineering and Automation,Shanghai University, Shanghai 200072,China.

Topology management is crucial to the efficiency of a wireless communication network in which all nodes are energy *** is a kind of energy efficient algorithm,while using a virtual backbone constructed by Connected Dominating Set(CDS) to organize the nodes is abetter *** an energy efficient Clustering algorithm based on Local CDS construction(CLCDS) to form the CDS-based backbone with local information *** this algorithm,each node builds its local spanningtree independently and computes its degree flagto determine whether to act as *** we elect the dominating nodes first and then connect them by a RNG[13]based algorithm,the number of border nodes and dominating nodes obtained by our algorithm is greatly reduced compared with previous *** correctness of the algorithm is proven and the efficiency is compared with other clustering heuristics using *** the cluster balance will have a significant impact on the networkperformance,we also provide with a tunable scheme to achieve a fairly balanced cluster distribution across the networks.

关键词： clustering algorithm connect domination set energy efficient algorithm graph theory

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A novel energy-efficient balanced multi-hop routing scheme (EBMRS) for wireless sensor networks EBMRS

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PEER-TO-PEER NETWORKING AND APPLICATIONS 2021年第2期14卷 807-820页

作者： Arora, Vishal Kumar Sharma, Vishal Dept Comp Sci Engn Shaheed Bhagat Singh State Tech CampusMoga Rd Ferozepur Punjab India Aston Univ Birmingham W Midlands England SBSSTC Dept Elect & Commun Ferozepur Punjab India

Wireless Sensor Network has been recognized as an attractive candidate among the telecommunication, meteorology, and sensor industries for the last few years owing to its wide range of applications, including environmental- and industrial-monitoring. In this paper, the authors propose an energy Balanced Multi-hop Routing Scheme (EBMRS) at both the inter- and intra-clustering level to discover the optimal route to the Base Station (BS) for maximizing energy efficiency. It selects the required number of sensor nodes as Cluster-Heads (CHs) based on their Probability of Selection (PS) metrics like the residual energy, the number of hop-counts, and the distance to the BS. Inside inter-cluster communication, each sensor node decreases their energy consumption by using nearest intermediate sensor node to communicate with the CH. During intra-cluster communication, CHs adopt multi-hop approach to transmit the aggregated data to the BS by finding a suitable CH that locates on the way to the BS. Moreover, to avoid unbalance cluster-formation, EBMRS ensure that the CHs locate at a minimum distance from each other. The outcomes report an improvement of a minimum of 40% in the network's lifetime of the demonstrated WSN network employed with the proposed EBMRS strategy in distinction with the existing energy-efficient routing approaches.

关键词： Wireless Sensor Network energy efficient algorithm Routing Clustering

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Tree Based energy efficient Routing Scheme for Body Area Network 2

Tree Based Energy Efficient Routing Scheme for Body Area Net...

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International Conference on Advances in Computer Engineering and Applications (ICACEA)

作者： Juneja, Priya Jain, Sushma Thapar Univ CSED Patiala Punjab India

ISBN: (纸本)9781467369114

Evolution of technology and day by day advancements in telecommunication, wireless communication, wireless sensors, and other technologies has led to development of such miniaturized sensors which can be implanted in or on the human body. This innovative and exhilarating area of research is Wireless Body Area Network (WBAN). Low power consumption and reliable data transmission is primary requirement in medical systems using WBAN. In this paper, we firstly explore efficient routing algorithm for WBAN and then it is modified to add energy factor with respect to routing gradient, energy aware expected transmission. energy efficient Tree Routing (EETR) algorithm is proposed for WBAN and it is compared with Ad-hoc On Demand Distance Vector Routing (AODVR) algorithm. This algorithm can jointly address the issue of low-power consumption and end-to end delay for reliable data transmission by modifying current algorithm so that nodes can robustly choose routing paths by minimizing the power levels for transmission. Considerable experiments are conducted using OMNET++ 4.5 as environment to ensure the successful implementation of proposed EETR algorithm by measuring number of factors like power consumption and Packet Reception Ratio (PRR). Experimental result analysis shows that EETR algorithm is beneficial than AODVR algorithm for energy efficient health monitoring using WBANs. In particular, single hop star topology and tree based multi-hop tree topology is compared with the help of extensive experiments conducted.

关键词： Body area network energy efficient algorithm multi-hop single-hop Tree based routing

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Fuzzy based multi-criteria based cluster head selection for enhancing network lifetime and efficient energy consumption

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CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE 2024年第4期36卷 e7921-e7921页

作者： Srivastava, Ankita Mishra, Pramod Kumar Banaras Hindu Univ Inst Sci Dept Comp Sci Varanasi India

Sensors plays an important role in day-to-day life as they sense and transfer data on the cloud and servers. These sensors have limited battery power due to which their optimized use is preferred with efficient energy consumption. As sensors were deployed almost everywhere under-earth, underwater, electronic devices, and mobiles thus their enhanced performance is really important. In WSN, clustering is considered to be an essential approach that gives various advantages such as efficient energy, stability period, network lifetime, less delay, and scalability but has an issue of hot-spot or energy-hole problems. For this Un-Equal Clustering is proposed where the size of clusters varies directly to the distance of the B.S. (Base Station). The main objective of Un-Equal clustering is energy consumption, hot-spot problem, and load balance among the cluster heads. In this paper, we have proposed an improved fuzzy-based multi-attributes un-equal clustering to overcome the problem of hot-spot problem. Earlier, researchers considered two attributes for selecting cluster heads (CHs), but later some of the MADM approaches were used that considered multiple attributes for optimal cluster head selection. In this paper, we have applied the fuzzy-based TOPSIS method for optimized Un-Equal clustering where the optimal node deployments with load balance among sensor nodes having optimal coverage and connectivity is considered. The results of the proposed method validate that it is one of the effective ways for selecting optimal cluster heads using fuzzy-based multi-attributes. Fuzzy-based TOPSIS for cluster heads selection method shows 37% enhanced network performance with other compared existing algorithms. The performance of the proposed method is evaluated in terms of network stability, packet delivery, energy consumption, and network lifetime and F-MAUC (Fuzzy based multi-attributes un-equal clustering) outperforms all other compared algorithms.

关键词： energy efficient algorithm fuzzy logic network lifetime un-equal clustering wireless sensor networks

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New online algorithm for dynamic speed scaling with sleep state

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THEORETICAL COMPUTER SCIENCE 2015年 593卷 79-87页

作者： Kumar, Gunjan Shannigrahi, Saswata Indian Inst Technol Guwahati Dept Comp Sci & Engn Gauhati Assam India

We consider an energy-efficient scheduling problem where n jobs J(1), J(2), ..., J(n) in need to be executed such that the total energy usage by these jobs is minimized while ensuring that each job is finished within its deadline. The processor executing these jobs can be in either active or sleep state at any point of time. The speed of the processor in an active state can be arbitrary. If the processor is running at a speed s >= 0, the required power P(s) is assumed to be equal to s(alpha) + g where alpha > 1, g > 0 are constants. On the other hand, the required power is zero when the processor is in the sleep state. However, L > 0 amount of wake-up energy is needed to wake-up the processor from the sleep state to the active state. In this paper, we work in an online setting where a job is known only at its arrival time, along with its processing volume and deadline. In such a setting, the currently best-known algorithm by Han et al. (2010) [3] provides a competitive ratio max{4, 2 + alpha(alpha)} of energy usage. We present a new online algorithm SqOA which provides a competitive ratio max{4, 2 + (2 - 1/alpha)(alpha)2(alpha-1)} of energy usage. For alpha >= 2.34, the competitive ratio of our algorithm is better than that of any other existing algorithm for this problem. (C) 2015 Elsevier B.V. All rights reserved.

关键词： energy efficient algorithm Online algorithm Scheduling algorithm

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On the NP-hardness of speed scaling with sleep state

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THEORETICAL COMPUTER SCIENCE 2015年 600卷 1-10页

作者： Kumar, Gunjan Shannigrahi, Saswata Indian Inst Technol Dept Comp Sci & Engn Gauhati India

A modern processor can dynamically set its speed while it is active, and can make a transition to sleep state when required. When the processor is operating at a speed s, the energy consumed per unit time is given by the power function P(s) = S-alpha + beta where alpha and beta are constants satisfying alpha > 1, beta > 0. No energy is consumed when the processor is in the sleep state. However, C> 0 units of energy are required to make a transition from the sleep state to the active state. The jobs are specified by their arrival time, deadline and the processing volume. We consider a scheduling problem, called speed scaling with sleep state, where each job has to be scheduled within its arrival time and deadline, and the goal is to minimize the total energy consumption required to process these jobs. Albers and Antoniadis (2012) proved the NP-hardness of this problem by reducing the NP-hard partition problem to an instance of this scheduling problem. The instance of this scheduling problem consists of the arrival time, the deadline and the processing volume for each of the jobs, in addition to some specifically designed P and C that depend on the instance of the partition problem. In this paper, we extend the above proof to show that the speed scaling with sleep state problem remains NP-hard for any fixed positive number C and any non-decreasing twice-differentiable strictly convex function P satisfying P (0) > 0. One example of such a function is the power function P (s) = S-alpha + beta, alpha > 1, beta > 0. (C) 2015 Elsevier B.V. All rights reserved.

关键词： energy efficient algorithm Scheduling algorithm NP-hardness

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A Reliable Lightweight Trust Evaluation Scheme for IoT Security

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INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS 2021年第11期12卷 723-731页

作者： Aldawsari, Hamad Artoli, Abdel Monim King Saud Univ Dept Comp Sci Coll Comp & Informat Sci Riyadh 11543 Saudi Arabia

The rapid development of smart devices and the consequent demand their reliability have posed many challenges limiting their versatility. One of the most significant challenges is safeguarding the widespread network of sensors and devices within harsh remote environments. Numerous trust schemes have been proposed to overcome related IoT security concerns. However, most of these schemes are not lightweight and consequently are not energy-efficient. This paper proposes a reliable lightweight trust evaluation scheme (RTE) to mitigate the malicious behavior of the nodes within IoT networks. The nodes are grouped into a set of clusters each having a cluster head while cluster members are categorized by evaluating their associated residual energy. Nodes with residual energy lower than the threshold (which is determined by the base station) are suspended until they recover and regain their activity. The computations are handled by the CH which is elected by an algorithm according to its energy and coverage degree in order to optimize the energy consumption in the network. For validation and performance evaluation, the proposed RTE scheme was compared to three of the recent schemes in its category. The obtained results have revealed that the proposed RTE scheme outperforms all of them in terms of detection rate, trust evaluation time, and energy efficiency.

关键词： IoT security clustering trust energy efficient algorithm

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Robust multi-objective multi-humanoid robots task allocation based on novel hybrid metaheuristic algorithm

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APPLIED INTELLIGENCE 2019年第12期49卷 4097-4127页

作者： Saeedvand, Saeed Aghdasi, Hadi S. Baltes, Jacky Univ Tabriz Fac Elect & Comp Engn Dept Informat Technol Tabriz Iran Univ Tabriz Fac Elect & Comp Engn Dept Comp Engn Tabriz Iran Natl Taiwan Normal Univ Dept Elect Engn Taipei Taiwan

Nowadays humanoid robots have generally made dramatic progress, which can form a coalition replacing human work in dangerous environments such as rescue, defense, exploration, etc. In contrast to other types of robots, humanoid robots' similarity to human make them more suitable for performing such a wide range of tasks. Rescue applications for robots, especially for humanoid robots are exciting. In rescue operating conditions, tasks' dependencies, tasks' repetitive accomplishment requirements, robots' energy consumption, and total tasks' accomplishment time are key factors. This paper investigates a practical variant of the Multi-Robots Task Allocation (MRTA) problem for humanoid robots as multi-humanoid robots' task allocation (MHTA) problem. In order to evaluate relevant aspects of the MHTA problem, we proposed a robust Multi-Objective Multi-Humanoid Robots Task allocation (MO-MHTA) algorithm with four objectives, namely energy consumption, total tasks' accomplishment time, robot's idle time and fairness were optimized simultaneously in an evolutionary framework in MO-MHTA, which address for the first time. MO-MHTA exhibits multi-objective properties in real-world applications for humanoid robots in two phases. In the first phase, the tasks are partitioned in a fair manner with a proposed constraint k-medoid (CKM) algorithm. In the second phase, a new non-dominated sorting genetic algorithm with special genetic operators is applied. Evaluations based on extensive experiments on the newly proposed benchmark instances with three robust multi-objective evolutionary algorithms (MOEAs) are applied. The proposed algorithm achieves favorable results in comparison to six other algorithms. Besides, the proposed algorithm can be seen as benchmark algorithms for real-world MO-MHTA instances.

关键词： Multi-humanoid robots Multi-objective problem Task allocation energy efficient algorithm

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