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Energy and Quality Aware Multi-Objective Resource Allocation algorithm in Cloud

JOURNAL OF INFORMATION & KNOWLEDGE MANAGEMENT 2021年第4期20卷

作者： Desire, Kone Kigninman Dhib, Eya Tabbane, Nabil Asseu, Olivier Ecole Super Africaine TIC ESATIC LASTIC Abidjan Cote Ivoire Univ Carthage SUPCOM MEDIATRON Lab Tunis Tunisia Inst Polytech Felix Houphouet Boigny INPHB Yamoussoukro Cote Ivoire

Cloud gaming has become the new service provisioning prototype that hosts the video games in the cloud and broadcasts the interactive game streaming to the players through the Internet. Here, the cloud must use massive resources for video representation and its streaming when several simultaneous players reach a particular point. Alternatively, various players may have separate necessities on Quality-of Experience, like low delay, high-video quality, etc. The challenging task is providing better service by the fixed cloud resource. Hence, there is a necessity for an energy-aware multi-resource allocation in the cloud. This paper devises a Fractional Rider-harmony search algorithm (Fractional Rider-HSA) for resource allocation in the cloud. The Fractional Rider-HSA combines fractional calculus, Rider Optimization algorithm (ROA), and HSA. Moreover, the fitness function, like mean opinion score (MOS), gaming experience loss, fairness, energy consumption, and network parameters, is considered to determine the optimal resource allocation. The proposed model produces the maximal MOS of 0.8961, maximal gaming experience loss (QE) of 0.998, maximal fairness of 0.9991, the minimum energy consumption of 0.3109, and minimal delay 0.2266, respectively.

关键词： Cloud computing fractional calculus spark architecture harmony search algorithm rider optimization algorithm

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Adaptive Multi-Hop Routing algorithm Based on harmony search in WSNs 9

Adaptive Multi-Hop Routing Algorithm Based on Harmony Search...

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9th International Conference on Advanced Infocomm Technology (ICAIT)

作者： Wang, Xuan Wang, Weidong Li, Xiuhua Wang, Chaowei Qin, Cai Beijing Univ Posts & Telecommun Informat & Elect Technol Lab Beijing Peoples R China

ISBN: (纸本)9781538636282

In Wireless sensor networks (WSNs), a lot of nodes with limited batteries are difficult to recharge power supplies. Therefore, an efficient management of energy for routing scheme is essential to prolonging the network lifetime, which is a NP-hard problem to overcome. In this paper, we propose an adaptive multi-hop routing algorithm (AMRA) to reduce the energy consumption and get energy balance in the whole network based on harmony search algorithm. The studies on AMRA employ a novel encoding scheme to transform multi-hop routing path into unequal matrix. To control the convergence speed and precision, AMRA adopts dynamic parameters and new search method to strengthen the local and global harmony search ability. The fitness function taking energy consumption, path length and residual energy into consideration tries to find the global optimal solution. The simulation results demonstrate that the AMRA performs better than the existing algorithms in terms of network lifetime, energy consumption and energy balance.

关键词： WSNs routing harmony search algorithm energy efficiency network lifetime

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FLIHSBC: Fuzzy Logic and Improved harmony search Based Clustering algorithm for Wireless Sensor Networks to Prolong the Network Lifetime 11th

FLIHSBC: Fuzzy Logic and Improved Harmony Search Based Clust...

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11th International Conference on Ubiquitous Computing and Ambient Intelligence (UCAmI)

作者： Agrawa, Deepika Pandey, Sudhakar Natl Inst Technol Raipur Dept IT Raipur Madhya Pradesh India

ISBN: (纸本)9783319675855;9783319675848

Wireless sensor networks (WSNs) is a rapidly growing technology. WSNs comprises of sensor nodes having limited energy as battery powers them. These batteries cannot be changed or recharged as they are operated in a harsh environment. Energy conservation mechanism should be developed. Through study, it is found that clustering is an approach for achieving energy efficiency. In this type of protocols, cluster heads (CH) are chosen among the sensor nodes and then clusters are formed by assigning non-cluster head to the nearest cluster head. Load balancing and the distribution of the cluster heads are the major drawbacks. To deal with the mentioned difficulties, a double optimization based on fuzzy logic approach and harmony search algorithm is proposed in this paper known as fuzzy logic and improved harmony search based clustering (FLIHSBC) algorithm. The proposed algorithm not only balances the energy consumption but also helps in maximizing the network lifetime. Simulation results proved that the proposed algorithm performs better in prolonging the lifetime of the sensor network.

关键词： Wireless sensor networks Energy optimization harmony search algorithm Fuzzy logic Clustering

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OPTIMIZATION-DRIVEN DEEP RECURRENT NEURAL NETWORK FOR INTRUSION DETECTION AND HEALTH RISK ASSESSMENT IN WIRELESS BODY SENSOR NETWORK

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BIOMEDICAL ENGINEERING-APPLICATIONS BASIS COMMUNICATIONS 2021年第1期33卷

作者： Alameen, Abdalla Gupta, Ashu Prince Sattam Bin Abdulaziz Univ Coll Arts & Sci Dept Comp Sci Wadi Al Dawasir Saudi Arabia

Wireless body sensor network (WBSN) has gained great attention in the environmental and military applications, but security is the major issue, nowadays. In addition, the data exchanged through the wireless sensor network (WSN) is vulnerable to several malicious attacks because of the physical defense equipment needs. Hence, various intrusion detection methods are required for defending against such attacks. Accordingly, an effective method, named deep recurrent neural network (Deep RNN), is proposed in this research for detecting the intrusion in WBSN. At first, the WBSN nodes are utilized to sense the data from the health records of patient for acquiring certain parameters to make risk assessment. Then, WBSN nodes transmit the data to the target nodes using the obtained parameters. After the determination of parameters, the WBSN nodes are responsible to collect the information of the patient and transfer the obtained information to cluster heads (CHs) based on the hybrid harmony search algorithm-particle swarm optimization (HSA-PSO). HSA-PSO is utilized for identifying the optimal CH node iteratively. From the selected CHs, secure communication is done to exchange the data packets. After that, the KDD features are extracted and intrusion detection is done using the proposed Deep RNN. After the genuine users are detected, the classification is done using fractional cat-based salp swarm algorithm (FCSSA) for the risk assessment. The performance of the intrusion detection and health risk assessment in WBSN based on the proposed model is evaluated based on accuracy, sensitivity, and the specificity. The developed model achieves the maximal accuracy of 95.79%, maximal sensitivity of 95.97%, and the maximal specificity of 95.61% using Cleveland dataset.

关键词： Wireless body sensor network Deep recurrent neural network harmony search algorithm Salp swarm algorithm Particle swarm optimization

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Study on HS-RNN in Vibration Prediction of Mechanical Spindle

Study on HS-RNN in Vibration Prediction of Mechanical Spindl...

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第33届中国控制与决策会议

作者： Jinxiang Pian Masuma Rifah Tamanna Alkasim Usman ABDULMAJID Academy School of Information and Control Engineering Shenyang Jianzhu University International school Shenyang Jianzhu University

Mechanical spindle in the high-speed operation due to an uneven distribution of the rotor mass,causing the spindle to vibrate thus affecting its ***,the model of mechanical spindle vibration prediction is of great *** mechanism of mechanical spindle vibration prediction is complex,and the amplitude of vibration varies nonlinearly with the *** is difficult to establish accurate model of mechanical spindle vibration *** this paper,RNN(Recurrent Neural Network) recurrent neural network is used to establish the model of mechanical spindle vibration *** vibration amplitude of the built-in balance block at different positions and spindle speeds is *** search(HS)Through self-learning update,thereby improving the accuracy of the mechanical spindle vibration prediction *** experimental results show that the HS-RNN-based mechanical spindle vibration prediction method proposed in this paper can automatically determine the network structure and accurately predict the vibration amplitude of the mechanical spindle.

关键词： harmony search algorithm RNN Recurrent Neural Network Vibration Prediction Mechanical Spindle

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A dynamic harmony search-based fuzzy clustering protocol for energy-efficient wireless sensor networks

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ANNALS OF TELECOMMUNICATIONS 2018年第5-6期73卷 353-365页

作者： Alia, Osama Moh'd Univ Tabuk Fac Comp & Informat Technol Dept Comp Sci POB 741 Tabuk 71491 Saudi Arabia

In the development of cluster-based energy-efficient protocols for wireless sensor networks (WSNs), a particularly challenging problem is the dynamic organization of sensors into a wireless communication network and the routing of sensed information from the field sensors to a remote base station (BS) in a manner that prolongs the lifetime of WSNs. This paper presents a new energy-efficient clustering protocol for WSNs, which can minimize total network energy dissipation while maximizing network lifetime. The protocol is divided into two parts. The first deals with constructing an infrastructure for the given WSN. A newly developed algorithm, based on a harmony search (HS), automatically determines the optimal number of clusters and allocates sensors into these clusters. This algorithm also eliminates the need to set the number of clusters a priori. The second part is concerned with the process of sending sensed data from nodes to their cluster head and then to the BS. A decentralized fuzzy clustering algorithm is proposed, where the selection of cluster heads in each round is locally made in each cluster during the network lifetime. Simulation results demonstrate that the proposed protocol can achieve an optimal number of clusters, prolong the network lifetime and increase the data delivery at the BS, when compared to other well-known clustering-based routing protocols.

关键词： Wireless sensor networks Energy-efficient routing protocols harmony search algorithm Fuzzy clustering

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Femur Bone Volumetric Estimation for Osteoporosis Classification Using Optimization-Based Deep Belief Network in X-Ray Images

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COMPUTER JOURNAL 2019年第11期62卷 1656-1670页

作者： Shankar, N. Sathish Babu, S. Viswanathan, C. Saveetha Engn Coll Dept Biomed Engn Chennai 602105 Tamil Nadu India Annamalai Univ Dept Elect & Instrumentat Engn Chidambaram 608002 Tamil Nadu India GRT Inst Engn & Technol Dept Elect & Commun Engn Tiruttani 631209 Tamil Nadu India

Osteoporosis classification is a significant requirement in the medical field to automatically classify the patients with skeleton disorder that occurs as a result of aging. The classification algorithms required improved accuracy and computationally less complexity. Accordingly, this paper proposes a classification method using the proposed gradient harmony search (GHS) optimization-based deep belief network. The GHS is developed by integrating the harmony search (HS) in the gradient descent (GD) algorithm. The osteoporosis classification is progressed as five major steps: preprocessing, segmentation using active shape model, geometric estimation using the proposed template search method, feature extraction for extracting the medical and image level features, and osteoporosis classification using the proposed GHS based deep belief network. The proposed template search method updates the geometric points of the femur segment effectively and automatically. Experimentation using the real-time database ensures the effectiveness of the proposed method in terms of accuracy, sensitivity, and specificity. The proposed method acquired the accuracy of 0.9539, proving that the osteoporosis classification using the proposed algorithm seems to be effective in taking accurate decisions regarding the patients.

关键词： femur bone osteoporosis classification deep belief network harmony search algorithm gradient search algorithm

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Intelligent computation techniques for optimization of the shortest path in an asynchronous network-on-chip

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CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS 2019年第1-Sup期22卷 335-346页

作者： Ilamathi, K. Rangarajan, P. RMD Engn Coll Chennai Tamil Nadu India

Network-on-chip (NoC) offers itself to be a suitable interconnection structure and as a viable alternative for system-on-chip, and hence is employed in very-large-scale integration (VLSI) design. An asynchronous network-on-chip (ANoC) design has low energy consumption because of the absence of the clock. However, obtaining optimal path routing in an asynchronous network-on-chip poses computational complexities. In this work, the shortest optimal paths are determined by employing five contemporary optimization techniques, including the harmony search (HS) algorithm using the Hopfield neural network (HNN) in an ANoC mesh topology. Using optimal parameters, in an ANoC, the energy consumption is significantly reduced and a faster convergence speed is achieved. The HS technique was found to have the least consumption of energy and time-complexity in the investigated techniques. HS technique outperformed all the other techniques in various aspects, making it the most suitable for determining the optimal shortest path.

关键词： Asynchronous network-on-chip Shortest path harmony search algorithm Energy consumption

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The impact of demand response programs on UPFC placement

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TURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES 2019年第6期27卷 4624-4639页

作者： Anari, Abbas Sharifi Nasab Ehsan, Mehdi Firuzabad, Mahmud Fotuhi Islamic Azad Univ Dept Elect & Comp Engn Sci & Res Branch Tehran Iran Sharif Univ Technol Dept Elect Engn Tehran Iran

Demand response (DR) and flexible AC transmission system (FACTS) devices can be effectively used for congestion management in power transmission systems. However, demand response program (DRP) implementation can itself affect the optimum location of FACTS devices, which is one of the main issues in power system planning. This paper investigates the impact of DRPs on unified power flow controller (UPFC) placement. The harmony search algorithm is employed to determine the optimum locations and parameter setting of UPFC in a long-term framework. The optimization problem is solved with different objectives including generation and congestion cost reduction, as well as loss reduction. In this paper, the proposed approach is analyzed using 5 different cases, which are defined in such a way that they demonstrate the impact of DRPs on the UPFC placement problem. The IEEE reliability test system is used as an illustrative example to demonstrate the necessity of considering DRPs for UPFC placement.

关键词： FACTS devices demand response programs harmony search algorithm congestion management loss reduction

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Towards Optimization of Metaheuristic algorithms for IoT Enabled Smart Homes Targeting Balanced Demand and Supply of Energy

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IEEE ACCESS 2019年 7卷 24267-24281页

作者： Kazmi, Saqib Javaid, Nadeem Mughal, Muhammad Junaid Akbar, Mariam Ahmed, Syed Hassan Alrajeh, Nabil COMSATS Inst Informat Technol Islamabad 44000 Pakistan Kyungpook Natl Univ Sch Comp Sci & Engn Daegu South Korea King Saud Univ Coll Appl Med Sci Riyadh 11633 Saudi Arabia

Internet of Things enabled smart grid (SG) is one of the most advanced technologies, which plays a key role in maintaining a balance between demand and supply by implementing demand response (DR) program. In SG, the main focus of the researchers is on home energy management (HEM) system, which is called demand side management. Appliance scheduling is an integral part of HEM system as it manages energy demand according to supply, by automatically controlling the appliances and shifting the load from peak to off peak hours. In this paper, the comparative performance of HEM controller embedded with heuristic algorithms, such as harmony search algorithm, enhanced differential evolution, and harmony search differential evolution, is evaluated. The integration of renewable energy source (RES) in SG makes the performance of HEM system more efficient. The electricity consumption in peak hours usually creates peaks and increases the cost but integration of RES makes the electricity consumer able to use the appliances in the peak hours. We formulate our problem using multiple knapsack theory that the maximum capacity of the consumer of electricity must be in the range, which is bearable for consumer with respect to electricity bill. Feasible regions are computed to validate the formulated problem. Finally, simulation of the proposed techniques is conducted in MATLAB to validate the performance of proposed scheduling algorithms in terms of cost, peak-to-average ratio, and waiting time minimization.

关键词： Smart grid knapsack enhanced differential evolution harmony search algorithm home energy management system demand side management

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