Md. Abdur Razzaque

Data-Centric Multiobjective QoS-Aware Routing Protocol for Body Sensor Networks

In this paper, we address Quality-of-Service (QoS)-aware routing issue for Body Sensor Networks (BSNs) in delay and reliability domains. We propose a data-centric multiobjective QoS-Aware routing protocol, called DMQoS, which facilitates the system to achieve customized QoS services for each traffic category differentiated according to the generated data types. It uses modular design architecture wherein different units operate in coordination to provide multiple QoS services. Their operation exploits geographic locations and QoS performance of the neighbor nodes and implements a localized hop-by-hop routing. Moreover, the protocol ensures (almost) a homogeneous energy dissipation rate for all routing nodes in the network through a multiobjective Lexicographic Optimization-based geographic forwarding. We have performed extensive simulations of the proposed protocol, and the results show that DMQoS has significant performance improvements over several state-of-the-art approaches.

Multi-Constrained QoS Geographic Routing for Heterogeneous Traffic in Sensor Networks

Sensor nodes report the sensed data packets to the sink and depending on the application these packets may have diverse attributes: time-critical (TC) and non time-critical (NTC). In such a heterogeneous traffic environment, designing a data dissemination framework that can achieve both the reliability and delay guarantee while preserving the energy efficiency, namely multi-constraint QoS (MCQoS), is a challenging problem. This paper proposes a new aggregate routing model and a localized algorithm (DARA) that implements the model. DARA is designed for multi-sink multipath location aware network architecture. Delay-differentiated multi-speed packet forwarding and in-node packet scheduling mechanisms are also incorporated with DARA. The simulation results demonstrate that DARA effectively improves the reliability, delay guarantee and energy efficiency.

Traffic Priority and Load Adaptive MAC Protocol for QoS Provisioning in Body Sensor Networks

Body sensor networks (BSNs) carry heterogeneous traffic types having diverse QoS requirements, such as delay, reliability and throughput. In this paper, we design a priority-based traffic load adaptive medium access control (MAC) protocol for BSNs, namely, PLA-MAC, which addresses the aforementioned requirements and maintains efficiency in power consumption. In PLA-MAC, we classify sensed data packets according to their QoS requirements and accordingly calculate their priorities. The transmission schedules of the packets are determined based on their priorities. Also, the superframe structure of the proposed protocol varies depending on the amount of traffic load and thereby ensures minimal power consumption. Our performance evaluation shows that the PLA-MAC achieves significant improvements over the state-of-the-art protocols.

ecMTCP: An Energy-Aware Congestion Control Algorithm for Multipath TCP

In this paper, we develop an energy-aware congestion control algorithm for multipath TCP, called ecMTCP. ecMTCP moves traffic from the most congested paths to the more lightly loaded paths, as well as from higher energy cost paths to the lower ones, thus achieving load-balancing and energy-savings. Our simulation results show that ecMTCP can achieve greater energy-savings compared to MPTCP, and preserve fairness to regular TCP.

An intelligent approach for virtual machine and QoS provisioning in cloud computing

Cloud Computing has become the most popular distributed computing environment because it does not require any user level management and controlling on the low-level implementation of the system. However, efficient resource provisioning is a key challenge for cloud computing and resolving such kind of problem can reduce under or over utilization of resources, increase user satisfaction by serving more users during peak hours, reduce implementation cost for providers and service cost for users. Existing works on cloud computing focuses to accurate estimation of the capacity needs, static or dynamic VM (Virtual Machine) creation and scheduling. But significant amount of time is required to create and destroy VMs which could be used to serve more user requests. In this paper, an adaptive QoS (Quality of Service) aware VM provisioning mechanism is developed that ensures efficient utilization of the system resources. The VM for similar type of requests has been recycled so that the VM creation time can be minimized and used to serve more user requests. In the proposed model, QoS is ensured by serving all the tasks within the requirements described in SLA. Tasks are separated using multilevel queue and the most urgent task is given high priority. The simulation-based experimental results shows that a great number of tasks can be served compared to others which will help to satisfy customers during the peak hour.

Congestion Avoidance and Fair Event Detection in Wireless Sensor Network

Summary Congestion in WSN increases the energy dissipation rates of sensor nodes as well as the loss of packets and thereby hinders fair and reliable event detection. We find that one of the key reasons of congestion in WSN is allowing sensing nodes to transfer as many packets as possible. This is due to the use of CSMA/CA that gives opportunistic medium access control. In this paper, we propose an energy efficient congestion avoidance protocol that includes source count based hierarchical and load adaptive medium access control and weighted round robin packet forwarding. We also propose in-node fair packet scheduling to achieve fair event detection. The results of simulation show our scheme exhibits more than 90% delivery ratio even under bursty traffic condition which is good enough for reliable event perception. Key words: Sensor Network, Congestion Avoidance, Hierarchical Medium Access, Fair Event Detection. 1. Introduction Wireless Sensor Networks (WSNs) are densely deployed for a wide range of applications in the military, health, environment, agriculture and smart office domain. These networks deliver numerous types of traffic, from simple periodic reports to unpredictable bursts of packets triggered by sensed events. Therefore, congestion happens due to contention caused by concurrent transmissions, buffer overflows and time varying wireless channel condition [1][2][3]. As WSN is a multi-hop network, congestion taking place at a single node may diffuse to the whole network and degrades its performance drastically [4]. Congestion causes many folds of drawbacks: (i) it increases energy dissipation rates of sensor nodes, (ii) it causes a lot of packet loss, which in turn diminish the network throughput, and (iii) it hinders fair event detections and reliable data transmissions. Therefore, congestion avoidance and fair packet delivery become a crucial research issue for the practical realization of WSN based envisioned applications.

Analysis of energy-tax for multipath routing in wireless sensor networks

Recently, multipath routing in wireless sensor networks (WSN) has got immense research interest due to its capability of providing increased robustness, reliability, throughput, and security. However, a theoretical analysis on the energy consumption behavior of multipath routing has not yet been studied. In this paper, we present a general framework for analyzing the energy consumption overhead (i.e., energy tax) resulting from multipath routing protocol in WSN. The framework includes a baseline routing model, a network model, and two energy consumption schemes for sensor nodes, namely, periodic listening and selective wake-up schemes. It exploits the influence of node density, link failure rates, number of multiple paths, and transmission environment on the energy consumption. Scaling laws of energy-tax due to routing and data traffic are derived through analysis, which provide energy profiles of single-path and multipath routing and serve as a guideline for designing energy-efficient protocols for WSN. The crossover points of relative energy taxes, paid by single-path and multipath routing, reception, and transmission, are obtained. Finally, the scaling laws are validated and performance comparisons are depicted for a reference network via numerical results.

QoS-aware distributed adaptive cooperative routing in wireless sensor networks

Abstract In this paper, we investigate a cooperative routing problem in time-varying Wireless Sensor Networks (WSNs) targeting the achievement of quality-of-service guarantees in delay and reliability domains. We develop a distributed adaptive cooperative routing protocol, called DACR, that exploits cooperative communication on top of delay- and energy-aware end-to-end routes and optimizes the trade-off between the reliability and delay through Lexicographic Optimization at each hop. We employ a lightweight reinforcement learning method to update the routing nodes with knowledge of expected performances that could be provided by the candidate relay nodes, helping to determine the optimal relay with the least overhead. The decision of selecting a transmission mode (i.e., direct or relayed transmission) at each hop is taken adaptively so that the reliability is maximized. The performances of our DACR have been evaluated through ns-2 simulations for a wide range of link failure rates and data traffic generation rates and the results show that the DACR outperforms a number of state-of-the-art protocols.

Reliable event detection and congestion avoidance in wireless sensor networks

Due to dense deployment and innumerable amount of traffic flow in wireless sensor networks (WSNs), congestion becomes more common phenomenon from simple periodic traffic to unpredictable bursts of messages triggered by external events. Even for simple network topology and periodic traffic, congestion is a likely event due to time varying wireless channel condition and contention caused due to interference by concurrent transmissions. Congestion causes huge packet loss and thus hinders reliable event perception. In this paper, we present a congestion avoidance protocol that includes source count based hierarchical medium access control (HMAC) and weighted round robin forwarding (WRRF). Simulation results show that our proposed schemes avoid packet drop due to buffer overflow and achieves more than 90% delivery ratio even under bursty traffic condition, which is good enough for reliable event detection.

A QoS and profit aware cloud confederation model for IaaS service providers

Cloud confederation is the union of cloud data centers that allows outsourcing user requests by a cloud provider during peak hours to liberate it from the constraint of limited physical resources. Federation extends some of the features of cloud like low cost, scalability, robustness and availability while increases the price and revenue of the providers along with maintaining a high QoS by effectively utilizing the resources of the data centers. Existing works on cloud federation do not consider all three categories of instances and hence cannot maximize their profits. Moreover, the process of establishing cloud federation and taking cost efficient decisions based on QoS parameters has not yet been provided in recent works. In this paper, we have designed a data communication model for the members of a cloud confederation, which exploits clear understanding of the usage pattern, types of requests in addition to infrastructure expenses. We develop an algorithm and a model for cost calculation, which enhances the decision making process over all the VM types (on-demand, reserved, spot) to increase resources utilization and profit. The simulation results, conducted on CloudSim, indicate that, our proposed model and algorithm enhances the profit, utilization, and QoS in a cloud confederation environment compared to a number of state-of-the-art approaches.