Manas Khatua

QoS-Guaranteed Bandwidth Shifting and Redistribution in Mobile Cloud Environment

Mobile cloud computing (MCC) improves the computational capabilities of resource-constrained mobile devices. On the other hand, the mobile users demand a certain level of quality-of-service (QoS) provisioning while they use services from the cloud, even if the interfacing gateway changes due to the mobility of the users. In this paper, we identify, formulate, and address the problem of QoS-guaranteed bandwidth shifting and redistribution among the interfacing gateways for maximizing their utility. Due to node mobility, bandwidth shifting is required for providing QoS-guarantee to the mobile nodes. However, shifting alone is not always sufficient for maintaining QoS-guarantee because of varying spectral efficiency across the associated channels, coupled with the corresponding protocol overhead involved with the computation of utility. We formulate bandwidth redistribution as a utility maximization problem, and solve it using a modified descending bid auction. In the proposed scheme, named as AQUM, each gateway aggregates the demands of all the connecting mobile nodes and makes a bid for the required amount of bandwidth. We investigate the existence of Nash equilibrium (NE) in the proposed solution. Theoretically, we deduce the maximum and minimum selling prices of bandwidth, and prove the convergence of AQUM. Simulation results establish the correctness of the proposed algorithm.

Semi-Distributed Backoff: Collision-Aware Migration from Random to Deterministic Backoff

Collision is imminent in wireless networks (WNs) capacitated with randomized distributed channel access. In such networks, the probability of frame drop (Pdrop) is greater than zero due to successive collisions with a finite retry limit m. The IEEE 802.11 DCF is one such widely accepted protocol used in wireless local area networks (WLANs). The objective of the work reported in this paper is to provide guaranteed channel access to colliding frames for avoiding successive collisions for any loss-sensitive application, and thus, increase network throughput under finite m. We propose the semi-distributed backoff (SDB) algorithm, which operates in two modes: S-mode and R-mode. The key idea of the SDB scheme is to perform receiver-side backoff, if a mobile station encounters collision even after performing the existing sender-side backoff procedures. Using the SDB scheme, we design Semi-DCF, a MAC protocol for WLANs, which performs opportunistic migration from random to deterministic backoff. Semi-DCF functions independent of m. This protocol exploits the collision detection capability of receivers for disseminating information on optimal backoffs to the contenders using signature vectors. An analysis of Semi-DCF using the 2D Markov chain, coupled with results of network simulation establishes its superior performance in WLANs.

Jamming in underwater sensor networks: detection and mitigation

Underwater sensor networks (UWSNs) can be deployed for sensing the environment in oceanographic columns and other water bodies in which they are deployed. The peculiar characteristic of the underwater medium, coupled with the queer nature of the sound waves in water, poses an enigmatic problem for UWSN researchers. In this study, the authors focus on the problem of UWSN jamming, which is a popular type of denial-of-service attack. The existing jamming detection solutions for sensor networks are primarily targeted towards the terrestrial ones. In this work, the authors study the unique characteristics of jamming in UWSN, and propose a protocol, known as underwater jamming detection protocol (UWJDP), to detect and mitigate jamming in underwater environments. The results show that if the packet delivery ratio (PDR) is less than or equal to 0.8, the authors have the maximum probability of detecting jamming. The jamming detection ratio is around 2-11- more for the said PDR.

Extracting mobility pattern from target trajectory in wireless sensor networks

Target tracking in wireless sensor networks is a well-known application. In real life scenario, target mobility can be predicted using well-known filters. In this paper, we explain an approach to model the pattern of movement of a target on the basis of target data available. This method utilizes filter techniques to predict the target and a curve-fitting algorithm to model the mobility of a target in both linear and non-linear motion patterns. Two alternate strategies to achieve mobility approximation have been proposed and compared. The efficacy of the algorithm is, further, adjudged by comparing its mobility prediction vis-a-vis the Kalman filter. Simulation results show that with sufficient data, the mobility pattern of the target can be fairly calculated even if the target moves unpredictably. Copyright

Residential Energy Management in Smart Grid: A Markov Decision Process-Based Approach

The deployment of advanced information and communication technologies has helped in the transformation of the traditional power grids into smart grids by introducing demand side management in residential area. The use of demand side management in the residential area can successfully reduce customers energy consumption, and can also provide a well balanced energy demand throughout the day. Based on real-time pricing information, a customer can shift his/her energy demand to reduce the energy consumption cost. In this paper, we present a Markov Decision Process (MDP)-based scheduling mechanism for residential energy management (REM) in smart grid. The aim of the proposed work is to reduce the energy expenses of a customer. In this mechanism, the Home Energy Management Unit (HEMU) acts as one of the players, the Central Energy Management Unit (CEMU) acts as another player. The HEMU interacts with the CEMU to fulfill its energy request within its desired budget. The CEMU follows its own dynamic pricing mechanism to decide the price per unit energy for on-peak and off-peak hours. The proposed mechanism is able to reduce the energy expenses of the residential customers.

D2D: Delay-Aware Distributed Dynamic Adaptation of Contention Window in Wireless Networks

The IEEE 802.11e enhanced distributed channel access (EDCA) protocol follows class-based service differentiation for providing differentiated quality-of-service (QoS). However, its collision avoidance mechanism using backoff algorithm can be inefficient for providing improved performance with respect to throughput and channel access delay, especially in a high network configuration (i.e. number of stations) with imperfect wireless channel. The existing and emerging works have devoted considerable attention on tuning the backoff parameters for achieving optimal throughput only. The prior works do not consider the channel access delay and throughput metrics altogether for performance improvement. Additionally, in most of the cases, the optimal configuration of backoff parameters are performed by a centralized controller. In this paper, we propose a delay-aware distributed dynamic adaptation of contention window scheme, namely D2D, for the cumulative improvement of both the throughput and the channel access delay at runtime. The D2D scheme requires two ad-hoc, distributed, and easy-to-obtain estimates-delay deviation ratio and channel busyness ratio-of the present delay level and channel congestion status of the network, respectively. A key advantage of the D2D scheme is that it is compliant with the IEEE 802.11 standard, and, thus, can be seamlessly integrable with the existing wireless card. We show the integrated model of the medium access control protocol, namely D2D Channel Access (D2DCA), for the IEEE 802.11e networks. We further propose a two-dimensional Markov chain model of the D2DCA protocol for analyzing its theoretical performance in saturated networks with imperfect wireless channel. Theoretical comparison with the benchmark protocols establishes the effectiveness of the D2DCA protocol.

Exploiting Partial-Packet Information for Reactive Jamming Detection: Studies in UWSN Environment

Reactive jamming in an underwater sensor network (UWSN) environment is a realistic and very harmful threat. It, typically, affects only a small part of a packet (not the entire one), in order to maintain a low detection probability. Prior works on reactive jamming detection were focused on terrestrial wireless sensor networks (TWSNs), and are limited in their ability to (a) detect it correctly, (b) distinguish the small corrupted part from the uncorrupted part of a packet, and (c) be adaptive with dynamic environment. Further, there is currently a need for a generalized framework for jamming detection that outlines the basic operations governing it. In this paper, we address these research lacunae by broadly designing such a framework for jamming detection, and specifically a detection scheme for reactive jamming. A key characteristic of this work is introducing the concept of partial-packet (PP) in jamming detection. The introduction of such an approach is unique – the existing works rely on holistic packet analysis, which degrades their performance – a fundamental issue that would substantially affect achieving real-time performance. We estimate the probability of high deviation in received signal strength (RSS) using a weak estimation learning scheme, which helps in absorbing the impact of dynamic environment. Finally, we perform CUSUM-test for reactive jamming detection. We evaluate the performance of our proposed scheme through simulation studies in UWSN environment. Results show that, as envisioned, the proposed scheme is capable of accurately detecting reactive jamming in UWSNs, with an accuracy of 100% true detection, while the average detection delay is substantially less.

Quality-assured Secured Load Sharing in Mobile Cloud Networking Environment

In mobile cloud networks (MCNs), a mobile user is connected with a cloud server through a network gateway, which is responsible for providing the required quality-of-service (QoS) to the users. If a user increases its service demand, the connecting gateway may fail to provide the requested QoS due to the overloaded demand, while the other gateways remain underloaded. Due to the increase in load in one gateway, the sharing of load among all the gateways is one of the prospective solutions for providing QoS-guaranteed services to the mobile users. Additionally, if a user misbehaves, the situation becomes more challenging. In this paper, we address the problem of QoS-guaranteed secured service provisioning in MCNs. We design a utility maximization problem for quality-assured secured load sharing (QuaLShare) in MCN, and determine its optimal solution using auction theory. In QuaLShare, the overloaded gateway detects the misbehaving gateways, and, then, prevents them from participating in the auction process. Theoretically, we characterize both the problem and the solution approaches in an MCN environment. Finally, we investigate the existence of Nash Equilibrium of the proposed scheme. We extend the solution for the case of multiple users, followed by theoretical analysis. Numerical analysis establishes the correctness of the proposed algorithms.

Packet-Centric Tradeoff and Unfair Success Region in IEEE 802.11 WLANs

In this paper, we present a packet-centric analytical study of carrier sense multiple access with collision avoidance (CSMA/CA)-based medium access in wireless local area networks, specifically using the IEEE 802.11 distributed coordination function (DCF). The packet-centric viewpoint of analysis adds a new dimension of insights over those available in the existing body of knowledge in this domain. We propose an absorbing Markov chain-based model for analyzing the behavior of head-of-line frames of each station in such networks. We generalize the long-term and short-term unfairness induced by the randomness of the DCF protocol and depict the actual unfair success region to be avoided in fair resource allocation schemes. One of the primary objectives of any CSMA/CA-based medium access control (MAC) protocol is to increase the frame delivery probability, while reducing the average delay of delivery. With such considerations, we show a tradeoff relationship between the delivery probability and access delay with respect to the maximum retransmission limit in a packet-centric approach. We numerically evaluate the packet-centric behavior of the DCF protocol for single-hop single access point networks involving both the saturated and unsaturated stations, imperfect wireless channel, and varying payload sizes.

MIRACLE: Mobility Prediction Inside a Coverage Hole Using Stochastic Learning Weak Estimator

In target tracking applications of wireless sensor networks (WSNs), one of the important but overlooked issues is the estimation of mobility behavior of a target inside a coverage hole. The existing approaches are restricted to networks with effective coverage by wireless sensors. Additionally, those works implicitly considered that a target does not change its mobility pattern inside the entire tracking region. In this paper, we address the above lacunae by designing a stochastic learning weak estimation-based scheme, namely mobility prediction inside acoverage hole (MIRACLE). The objectives of MIRACLE are two fold. First, one should be able to correctly predict the mobility pattern of a target inside a coverage hole with low computational overhead. Second, if a target changes its mobility pattern inside the coverage hole, the proposed estimator should give some estimation about all possible transitions among the mobility models. We use the trajectory extrapolation and fusion techniques for exploring all possible transitions among the mobility models. We validate the results with simulated traces of mobile targets generated using network simulator NS-2. Simulation results show that MIRACLE estimates the mobility patterns inside coverage hole with an accuracy of more than 60% in WSNs.