Babar Nazir

Mobile Sink based Routing Protocol (MSRP) for Prolonging Network Lifetime in Clustered Wireless Sensor Network

In WSN, sensors near the sink have to relay the data of the nodes away from the sink and as a result they drain their energy very quickly. It result in network partitioning and can significantly limit the network lifetime. This problem is termed as hotspot problem. Recently, formation of hot spot or energy hole near the sink has emerged as a critical issue for data gathering in WSN. In this paper, we address hotspot problem and purposed Mobile Sink based Routing Protocol (MSRP) for Prolonging Network Lifetime in Clustered Wireless Sensor Network. In MSRP, mobile sink moves in the clustered WSN to collect sensed data from the CHs within its vicinity. During data gathering mobile sink also maintains information about the residual energy of the CHs. Mobile sink based on the residual energy of CHs move to the CHs having higher energy. Consequently, the hotspot problem is minimized as the immediate neighbor of the sink is high energy node and it changes because of regular sink movement. It results in a balanced use of WSN energy and improves network life time. To evaluate the performance of the proposed strategy intensive simulation are carried out using OMNet-4.0. Performance of the proposed strategy is compared to the static sink and multiple sinks strategies, using metrics such as energy per packet, and throughput. The simulation results demonstrate that MSRP is effective in prolonging the network lifetime as well as in improving throughput than static sink and multiple sink strategies.

Resource management in cloud computing

Cloud computing has emerged as a popular computing paradigm for hosting large computing systems and services. Recently, significant research is carried out on Resource Management (RM) techniques that focus on the efficient sharing of cloud resources among multiple users. RM techniques in cloud are designed for computing and workload intensive applications that have different optimization parameters. This study presents a comprehensive review of RM techniques and elaborates their extensive taxonomy based on the distinct features. It highlights evaluation parameters and platforms that are used to evaluate RM techniques. Moreover, it presents design goals and research challenges that should be considered while proposing novel RM techniques.

Adaptive checkpointing strategy to tolerate faults in economy based grid

In this paper, we develop a fault tolerant job scheduling strategy in order to tolerate faults gracefully in an economy based grid environment. We propose a novel adaptive task checkpointing based fault tolerant job scheduling strategy for an economy based grid. The proposed strategy maintains a fault index of grid resources. It dynamically updates the fault index based on successful or unsuccessful completion of an assigned task. Whenever a grid resource broker has tasks to schedule on grid resources, it makes use of the fault index from the fault tolerant schedule manager in addition to using a time optimization heuristic. While scheduling a grid job on a grid resource, the resource broker uses fault index to apply different intensity of task checkpointing (inserting checkpoints in a task at different intervals).To simulate and evaluate the performance of the proposed strategy, this paper enhances the GridSim Toolkit-4.0 to exhibit fault tolerance related behavior. We also compare “checkpointing fault tolerant job scheduling strategy” with the well-known time optimization heuristic in an economy based grid environment. From the measured results, we conclude that even in the presence of faults, the proposed strategy effectively schedules grid jobs tolerating faults gracefully and executes more jobs successfully within the specified deadline and allotted budget. It also improves the overall execution time and minimizes the execution cost of grid jobs.

Fault Tolerant Job Scheduling in Computational Grid

In large-scale grids, the probability of a failure is much greater than in traditional parallel systems [I]. Therefore, fault tolerance has become a crucial area in grid computing. In this paper, we address the problem of fault tolerance in term of resource failure. We devise a strategy for fault tolerant job scheduling in computational grid. Proposed strategy maintains history of the fault occurrence of resource in grid information service (GIS). Whenever a resource broker has job to schedule it uses the resource fault occurrence history information from GIS and depending on this information use different intensity of check pointing and replication while scheduling the job on resources which have different tendency towards fault. Using check pointing proposed scheme can make grid scheduling more reliable and efficient. Further, it increases the percentage of jobs executed within specified deadline and allotted budget, hence helping in making grid trustworthy. Through simulation we have evaluated the performance of the proposed strategy. The experimental results demonstrate that proposed strategy effectively schedule the grid jobs in fault tolerant way in spite of highly dynamic nature of grid

Energy balanced clustering in wireless sensor network

In this paper, clustering in terms of energy efficiency in WSN is explored and proposed Energy Balanced Clustering in Wireless Sensor Network (EBC). Algorithms for energy balanced cluster formation, cluster head selection, intra cluster and inter cluster communication in WSN are proposed. Furthermore, using OMNet-4.0 simulation performance of proposed protocol is compared with LEACH and EEMC using parameters like energy per packet and throughput. Simulation results demonstrate that EBC is effective in prolonging the network lifetime as well as in improving throughput, than LEACH and EEMC.

Performance evaluation of fault tolerance techniques in grid computing system

As fault tolerance is the ability of a system to perform its function correctly even in the presence of faults. Therefore, different fault tolerance techniques (FTTs) are critical for improving the efficient utilization of expensive resources in high performance grid computing systems, and an important component of grid workflow management system. This paper presents a performance evaluation of most commonly used FTTs in grid computing system. In this study, we considered different system centric parameters, such as throughput, turnaround time, waiting time and network delay for the evaluation of these FTTs. For comprehensive evaluation we setup various conditions in which we vary the average percentage of faults in a system, along with different workloads in order to find out the behavior of FTTs under these conditions. The empirical evaluation shows that the workflow level alternative task techniques have performance priority on task level checkpointing techniques. This comparative study will help to grid computing researchers in order to understand the behavior and performance of different FTTs in detail.

Energy efficient and QoS aware routing protocol for Clustered Wireless Sensor Network

In this paper, a protocol called Energy Efficient and QoS aware Routing (EEQR) protocol for Clustered Wireless Sensor Network is proposed. To ensure QoS for different traffic types, prioritization of data is done based on message type and content. To address energy efficiency (hotspot problem) and high end-to-end delay problem, a combination of mobile and static sink is used for data gathering. Delay sensitive message are sent through the static sink and delay tolerant message are send through the mobile sink. Consequently, EEQR incurs less end-to-end delay, is energy efficient as well as able to ensure QoS. To evaluate the performance of the proposed strategy, intensive simulations are carried out. Performance of the proposed strategy is compared with the static sink and mobile sinks strategies. The results demonstrated that EEQR has prolonged the network and coverage lifetime, as well as has improved the other QoS routing parameters, such as delay, packet loss ratio, and throughput.

Dynamic sleep scheduling for minimizing delay in wireless sensor network

Dynamic Sleep Scheduling (DSS) for Minimizing Delay in Wireless Sensor Network is proposed. To reduce delay, DSS identifies nodes for different sleep/wake according to their traffic load at two levels: a) Nodes with different sleep/wake schedule requirement according to their different traffic load based on their topological importance in the network. b) Nodes with different sleep/wake schedule based on handling burst traffic in the proximity of event occurrence node. It then assign different active interval to the nodes, according to their variable traffic load requirement defined by node topological importance and by handling burst traffic in the proximity of event occurrence node. Using these heuristics DSS reduces end-to-end delay and minimize energy per packet by minimizing the congestion at nodes having heavy traffic load. Simulations are carried out to evaluate the performance of the proposed protocol, by comparing its performance with S-MAC and anycast protocols. Simulation results demonstrated that the proposed protocol has significantly reduced the end-to-end delay, as well as has improved average energy per packet.

Sleep/wake scheduling scheme for minimizing end-to-end delay in multi-hop wireless sensor networks

We present a sleep/wake schedule protocol for minimizing end-to-end delay for event driven multi-hop wireless sensor networks. In contrast to generic sleep/wake scheduling schemes, our proposed algorithm performs scheduling that is dependent on traffic loads. Nodes adapt their sleep/wake schedule based on traffic loads in response to three important factors, (a) the distance of the node from the sink node, (b) the importance of the nodes location from connectivitys perspective, and (c) if the node is in the proximity where an event occurs. Using these heuristics, the proposed scheme reduces end-to-end delay and maximizes the throughput by minimizing the congestion at nodes having heavy traffic load. Simulations are carried out to evaluate the performance of the proposed protocol, by comparing its performance with S-MAC and Anycast protocols. Simulation results demonstrate that the proposed protocol has significantly reduced the end-to-end delay, as well as has improved the other QoS parameters, like average energy per packet, average delay, packet loss ratio, throughput, and coverage lifetime.

A hybrid fault tolerance technique in grid computing system

In order to achieve high level of reliability and availability, the grid infrastructure should be a foolproof fault tolerant. Fault tolerance plays a key role in order to assert availability and reliability of a grid system. Since the failure of resources affects job execution fatally, fault tolerance service is essential to satisfy QoS requirement in grid computing.In this paper we proposed two hybrid fault tolerance techniques (FTTs) that are called alternate task with checkpoint and alternate task with retry. These proposed hybrid FTTs inherit the good features and overcome the limitations of workflow level FTT and task level FTT. We evaluate the performance of our proposed FTTs under different experimental environments. Finally, we conclude that alternate task with checkpoint improves the reliability of a grid system more significantly than alternate task with retry.