List of Articles Scheduling

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  1 - Optimal Sensor Scheduling Algorithms for Distributed Sensor Networks
  Behrooz Safarinejadian Abdolah Rahimi
  10.7508/jist.2013.03.004
  In this paper, a sensor network is used to estimate the dynamic states of a system. At each time step, one (or multiple) sensors are available that can send its measured data to a central node, in which all of processing is done. We want to provide an optimal algorithm More

  In this paper, a sensor network is used to estimate the dynamic states of a system. At each time step, one (or multiple) sensors are available that can send its measured data to a central node, in which all of processing is done. We want to provide an optimal algorithm for scheduling sensor selection at every time step. Our goal is to select the appropriate sensor to reduce computations, optimize the energy consumption and enhance the network lifetime. To achieve this goal, we must reduce the error covariance. Three algorithms are used in this work: sliding window, thresholding and randomly chosen algorithms. Moreover, we will offer a new algorithm based on circular selection. Finally, a novel algorithm for selecting multiple sensors is proposed. Performance of the proposed algorithms is illustrated with numerical examples. Manuscript profile
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  2 - Defense against SYN Flooding Attacks: A Scheduling Approach
  Shahram Jamali Gholam Shaker
  10.7508/jist.2014.01.007
  The TCP connection management protocol sets a position for a classic Denial of Service (DoS) attack, called the SYN flooding attack. In this attack attacker sends a large number of TCP SYN segments, without completing the third handshaking step to quickly exhaust connec More

  The TCP connection management protocol sets a position for a classic Denial of Service (DoS) attack, called the SYN flooding attack. In this attack attacker sends a large number of TCP SYN segments, without completing the third handshaking step to quickly exhaust connection resources of the victim server. Therefore it keeps TCP from handling legitimate requests. This paper proposes that SYN flooding attack can be viewed metaphorically as result of an unfair scheduling that gives more opportunity to attack requests but prevents legal connections from getting services. In this paper, we present a scheduling algorithm that ejects the half connection with the longest duration, when number of half open connections reaches to the upper bound. The simulation results show that the proposed defense mechanism improves performance of the under attack system in terms of loss probability of requests and share of regular connections from system resources. Manuscript profile
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  3 - Ant Colony Scheduling for Network On Chip
  Neda  Dousttalab Mohammad Ali Jabraeil Jamali Ali Ghaffari
  10.7508/jist.2015.02.004
  The operation scheduling problem in network on chip is NP-hard; therefore effective heuristic methods are needful to provide modal solutions. This paper introduces ant colony scheduling, a simple and effective method to increase allocator matching efficiency and hence n More

  The operation scheduling problem in network on chip is NP-hard; therefore effective heuristic methods are needful to provide modal solutions. This paper introduces ant colony scheduling, a simple and effective method to increase allocator matching efficiency and hence network performance, particularly suited to networks with complex topology and asymmetric traffic patterns. Proposed algorithm has been studied in torus and flattened-butterfly topologies with multiple types of traffic pattern. Evaluation results show that this algorithm in many causes has showed positive effects on reducing network delays and increased chip performance in comparison with other algorithms. Manuscript profile
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  4 - A Linear Model for Energy-Aware Scheduling Problem Considering Interference in Real-time Wireless Sensor Networks
  Maryam  Hamidanvar rafeh rafeh
  10.7508/jist.2015.04.007
  An important factor in increasing quality of service in real-time wireless networks is minimizing energy consumption, which contradicts with increasing message delivery rate because of associating a time deadline to each message. In these networks, every message has a t More

  An important factor in increasing quality of service in real-time wireless networks is minimizing energy consumption, which contradicts with increasing message delivery rate because of associating a time deadline to each message. In these networks, every message has a time deadline constraint and when the message is not delivered to its destination before its deadline constraint, it will drop. Therefore, scheduling methods that simultaneously consider both energy consumption and time deadline constraint are needed. An effective method for reducing energy consumption is multi-hop transmission of packets. However, this method takes longer time for transmission as compared to single-hop transmission. Parallel transmission is another approach which on one hand reduces the transmission time and on the other hand increases the network throughput. However, a main issue with parallel transmission is the presence of interference among nearby nodes. In this paper, we propose a linear model (ILP formulation) for energy aware scheduling problem in real-time wireless sensor networks using parallel transmission. The main objective of the model is to reduce energy consumption and packet loss using multi-hop routing and parallel transmission. Experimental results show that the proposed model finds the optimum solution for the problem and outperforms the sequential scheduling based on the TDMA protocol. Manuscript profile
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  5 - Hybrid Task Scheduling Method for Cloud Computing by Genetic and PSO Algorithms
  Amin Kamalinia Ali Ghaffari
  10.7508/jist.2016.04.008
  Cloud computing makes it possible for users to use different applications through the internet without having to install them. Cloud computing is considered to be a novel technology which is aimed at handling and providing online services. For enhancing efficiency in cl More

  Cloud computing makes it possible for users to use different applications through the internet without having to install them. Cloud computing is considered to be a novel technology which is aimed at handling and providing online services. For enhancing efficiency in cloud computing, appropriate task scheduling techniques are needed. Due to the limitations and heterogeneity of resources, the issue of scheduling is highly complicated. Hence, it is believed that an appropriate scheduling method can have a significant impact on reducing makespans and enhancing resource efficiency. Inasmuch as task scheduling in cloud computing is regarded as an NP complete problem; traditional heuristic algorithms used in task scheduling do not have the required efficiency in this context. With regard to the shortcomings of the traditional heuristic algorithms used in job scheduling, recently, the majority of researchers have focused on hybrid meta-heuristic methods for task scheduling. With regard to this cutting edge research domain, we used HEFT (Heterogeneous Earliest Finish Time) algorithm to propose a hybrid meta-heuristic method in this paper where genetic algorithm (GA) and particle swarm optimization (PSO) algorithms were combined with each other. The results of simulation and statistical analysis of proposed scheme indicate that the proposed algorithm, when compared with three other heuristic and a memetic algorithms, has optimized the makespan required for executing tasks. Manuscript profile
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  6 - BSFS: A Bidirectional Search Algorithm for Flow Scheduling in Cloud Data Centers
  Hasibeh Naseri Sadoon Azizi Alireza Abdollahpouri
  10.7508/jist.2019.03.002
  To support high bisection bandwidth for communication intensive applications in the cloud computing environment, data center networks usually offer a wide variety of paths. However, optimal utilization of this facility has always been a critical challenge in a data cent More

  To support high bisection bandwidth for communication intensive applications in the cloud computing environment, data center networks usually offer a wide variety of paths. However, optimal utilization of this facility has always been a critical challenge in a data center design. Flow-based mechanisms usually suffer from collision between elephant flows; while, packet-based mechanisms encounter packet re-ordering phenomenon. Both of these challenges lead to severe performance degradation in a data center network. To address these problems, in this paper, we propose an efficient mechanism for the flow scheduling problem in cloud data center networks. The proposed mechanism, on one hand, makes decisions per flow, thus preventing the necessity for rearrangement of packets. On the other hand, thanks do SDN technology and utilizing bidirectional search algorithm, our proposed method is able to distribute elephant flows across the entire network smoothly and with a high speed. Simulation results confirm the outperformance of our proposed method with the comparison of state-of-the-art algorithms under different traffic patterns. In particular, compared to the second-best result, the proposed mechanism provides about 20% higher throughput for random traffic pattern. In addition, with regard to flow completion time, the percentage of improvement is 12% for random traffic pattern Manuscript profile
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  7 - Energy Efficient Cross Layer MAC Protocol for Wireless Sensor Networks in Remote Area Monitoring Applications
  R Rathna L Mary Gladence J Sybi Cynthia V Maria Anu
  10.52547/jist.9.35.207
  20.1001.1.23221437.2021.9.35.6.5
  Sensor nodes are typically less mobile, much limited in capabilities, and more densely deployed than the traditional wired networks as well as mobile ad-hoc networks. General Wireless Sensor Networks (WSNs) are designed with electro-mechanical sensors through wireless d More

  Sensor nodes are typically less mobile, much limited in capabilities, and more densely deployed than the traditional wired networks as well as mobile ad-hoc networks. General Wireless Sensor Networks (WSNs) are designed with electro-mechanical sensors through wireless data communication. Nowadays the WSN has become ubiquitous. WSN is used in combination with Internet of Things and in many Big Data applications, it is used in the lower layer for data collection. It is deployed in combination with several high end networks. All the higher layer networks and application layer services depend on the low level WSN in the deployment site. So to achieve energy efficiency in the overall network some simplification strategies have to be carried out not only in the Medium Access Control (MAC) layer but also in the network and transport layers. An energy efficient algorithm for scheduling and clustering is proposed and described in detail. The proposed methodology clusters the nodes using a traditional yet simplified approach of hierarchically sorting the sensor nodes. Few important works on cross layer protocols for WSNs are reviewed and an attempt to modify their pattern has also been presented in this paper with results. Comparison with few prominent protocols in this domain has also been made. As a result of the comparison one would get a basic idea of using which type of scheduling algorithm for which type of monitoring applications. Manuscript profile
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  8 - TPALA: Two Phase Adaptive Algorithm based on Learning Automata for job scheduling in cloud Environment
  Abolfazl Esfandi Javad Akbari Torkestani Abbas Karimi Faraneh Zarafshan
  10.61186/jist.39109.12.45.29
  Due to the completely random and dynamic nature of the cloud environment, as well as the high volume of jobs, one of the significant challenges in this environment is proper online job scheduling. Most of the algorithms are presented based on heuristic and meta-heuristi More

  Due to the completely random and dynamic nature of the cloud environment, as well as the high volume of jobs, one of the significant challenges in this environment is proper online job scheduling. Most of the algorithms are presented based on heuristic and meta-heuristic approaches, which result in their inability to adapt to the dynamic nature of resources and cloud conditions. In this paper, we present a distributed online algorithm with the use of two different learning automata for each scheduler to schedule the jobs optimally. In this algorithm, the placed workload on every virtual machine is proportional to its computational capacity and changes with time based on the cloud and submitted job conditions. In proposed algorithm, two separate phases and two different LA are used to schedule jobs and allocate each job to the appropriate VM, so that a two phase adaptive algorithm based on LA is presented called TPALA. To demonstrate the effectiveness of our method, several scenarios have been simulated by CloudSim, in which several main metrics such as makespan, success rate, average waiting time, and degree of imbalance will be checked plus their comparison with other existing algorithms. The results show that TPALA performs at least 4.5% better than the closest measured algorithm. Manuscript profile