Artificial Intelligence
S. Tabatabaei; H. Nosrati Nahook
Abstract
Background and Objectives: With the recent progressions in wireless communication technology, powerful and costless wireless receivers are used in a variety of mobile applications. Mobile networks are a self-arranged network, which is including of mobile nodes that communicate with each other without ...
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Background and Objectives: With the recent progressions in wireless communication technology, powerful and costless wireless receivers are used in a variety of mobile applications. Mobile networks are a self-arranged network, which is including of mobile nodes that communicate with each other without a central control Mobile networks gained considerable attention due to the adaptability, scalability, and costs reduction. Routing and power consumption is a major problem in mobile networks because the network topology changes frequently. Mobile wireless networks suffer from high error rates, power constraints, and limited bandwidth. Due to the high importance of routing protocols in dynamic multi-hop networks, many researchers have paid attention to the routing problem in Mobile Ad hoc Networks (MANET). This paper proposes a new routing algorithm in MANETs which is based upon the Cuckoo optimization algorithm (COA).Methods: COA is inspired by the lifestyle of a family of birds called cuckoo. These birds’ lifestyle, egg-laying features, and breeding are the basis of the development of this optimization algorithm. COA is started by an initial population. There are two types of population of cuckoos in different societies: mature cuckoos and eggs. This algorithm tries to find more stable links for routing.Results: Simulation results prove the high performance of proposed work in terms of throughput, delay, hop count, and discovery time.Conclusion: The cuckoo search convergence is based on the establishment of the Markov chain model to prove that it satisfies the two conditions of the global convergence in a random search algorithm. Also, the cuckoo search that suitable for solving continuous problems and multi-objective problems. We have done a lot of experiments to verify the performance of the Cuckoo algorithm for routing in MANETs. The result of experiments shows the superiority of the proposed method against a well-known AODV algorithm.
Cloud Computing
H. Jahanpour; H. Barati; A. Mehranzadeh
Abstract
Background and Objectives: Cloud Computing has brought a new dimension to the IT world. The technology of cloud computing allows employing a large number of Virtual Machines to run intensive applications. Each failure in running applications fails system operations. To solve the problem, it is required ...
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Background and Objectives: Cloud Computing has brought a new dimension to the IT world. The technology of cloud computing allows employing a large number of Virtual Machines to run intensive applications. Each failure in running applications fails system operations. To solve the problem, it is required to restart the systems.Methods: In this paper, to predict and avoid failure in HPC systems, a method of fault tolerance to High-Performance Computing systems (HPC) in the cloud is called Daemon-COA-MMT (DCM), has been proposed. In the proposed method, the Daemon Fault Tolerance technique has been enhanced, and COA-MMT has been utilized for load balancing. The method consists of four modules, which are used to determine the host state. When the system is in the alarm state, the current host may face failure. Then the most optimal host for migration is selected, and process-level migration is performed. The method causes decreased migration overheads, decreased system performance speed, optimal use of underutilized hosts instead of leasing new hosts, appropriate load balancing, equal use of hardware resources by all hosts, focusing on QoS and SLA, and the significant decrease of energy consumption.Results: The simulation results revealed that in terms of parameters, the proposed method declines average job makespan, average response time, and average task execution cost by 18.06%, 35.68%, and 24.6%, respectively. The proposed fault tolerance algorithm has improved energy consumption by 30% and decreased the HPC systems' failure rate.Conclusion: In this study, the Daemon Fault Tolerance technique has been enhanced, and COA-MMT has been utilized for load balancing in high performance computing in the cloud computing.
Hardware
A. Oloomi; H. Khanmirza
Abstract
Background and Objectives: Nowadays, video hosting services receive and stream videos using standard protocols like Real-Time Messaging Protocol (RTMP). During the streaming process, video file streams are usually divided into small multi-second parts, and the player receives these parts instead of the ...
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Background and Objectives: Nowadays, video hosting services receive and stream videos using standard protocols like Real-Time Messaging Protocol (RTMP). During the streaming process, video file streams are usually divided into small multi-second parts, and the player receives these parts instead of the whole file at once. Most of the streaming protocols are capable of adaptive streaming and tolerating faults like device failures, and link disconnections. Faults might affect the performance of live streaming in terms of packet loss, latency, jitter, and video quality. The software-defined networking paradigm has also gained momentum in enterprise networks due to its lower-cost management and better network utilization. However, full migration from the current networks to the SDN model is not practical.Methods: The purpose of this study is to investigate the effectiveness of fault tolerance mechanisms of RTMP protocol on hybrid software-defined networks (SDN). In this paper, a practical and straightforward hybrid network architecture is proposed for gradual migration from traditional IP networks. Then, the performance of the RTMP protocol is compared for live video streaming on this network with different streams facing multiple failures.Results: Our experiments show that network failure recovery time in SDN is directly depends on the video stream recovery time while in traditional networks, streams need to be buffered again and it takes another several seconds due to the long interruption time. We propose an equation to give a rough estimation of data loss in SDN network during failures based on our observations which helps us in comparisons. We also demonstrate the average switching time in the SDN networks is almost half of the switching time in traditional networks.Conclusion: Our experiments proves, practically, video recovery time in SDN is less than a traditional network and has more correspondence with mechanisms of RTMP.
