Adnan Iqbal

Energy management in Wireless Sensor Networks

Energy management in Wireless Sensor Networks (WSNs) is of paramount importance for the remotely deployed energy stringent sensor nodes. These nodes are typically powered by attached batteries. Several battery-driven energy conservation schemes are proposed to ensure energy efficient network operation. The constraints associated to the limited battery capacity shifted the research trend towards finding alternate sources by harvesting ambient energy. This survey presents a high level taxonomy of energy management in WSNs. We analyze different battery-driven energy consumption based schemes and energy harvesting based energy provisioning schemes. We also highlight the recent breakthrough of wireless energy transference to a sensor node as an alternative to typical batteries. We recommend taking into account recent energy provisioning advancements in parallel with the traditional energy conservation approaches for a sensor network while designing energy efficient schemes.

Performance evaluation of OpenDaylight SDN controller

Enourmous amount of data has resulted into large data centres. Virtual machines and virtual networks are an integral part of large data centres. As a result, software defined network controllers have emerged as viable solution to manage such networks. The performance analysis of network controllers is generally carried out through benchmarking. Although several benchmarking studies exist, recently launched OpenDaylight SDN Controller is not considered in any benchmarking study yet. In this paper, we present initial results of benchmarking of Open-Daylight SDN Controller with well known Floodlight controller. We present latency and throughput results of OpenDaylight SDN Controller and Floodlight under different scenarios. We find that OpenDaylight SDN Controller has low average responses as compared to Floodlight. We also note that the standard benchmarking tool - Cbench - has no support for real traffic patterns in a data centre, since data centre traffic is considerably complex. In addition to benchmarking of OpenDaylight SDN Controller, we propose modifications in Cbench to accommodate models of real traffic in data centres. We also discuss our initial implementation.

Improving WSN Simulation and Analysis Accuracy Using Two-Tier Channel Models

Accurate simulation and analysis of wireless protocols and systems is inherently dependent on an accurate model of the underlying channel. In this paper, we show that residual MAC layer wireless sensor network (WSN) channels cannot be characterized using the commonly-used high-order Markov channel models. Instead, we demonstrate that 2-Tier models, in which a high-level (tier 1) frame-level model excites a lower-level (tier 2) bit-error model, are needed to accurately characterize WSN residual channels. We compare the modeling accuracy of 1-Tier and 2-Tier models using residual bit-error traces collected over an operational 802.15.4 network. We first analyze error traces collected over different setups to investigate the amount of bit-level memory present in wireless sensor network channels. We then validate the accuracy of the proposed models using information divergence measures. We show that 2- Tier models have significantly and consistently better accuracy than 1-Tier models. Finally, we demonstrate that the wrong choice of a channel model can result in grossly inaccurate simulation results. This claim is substantiated by simulating three important metrics: (i) recovery ratio for an abstract Forward Error Correction (FEC) scheme, (ii) frame goodput of an unreliable protocol over a multihop network, and (Hi) number of retransmissions per packet for a reliable protocol.

Topology Control for Harvesting Enabled Wireless Sensor Networks: A Design Approach

While there has been a lot of research on energy efficient topology control protocols destined for different applications, topology control has never been explored in the presence of harvesting enabled sensors. Largely, researchers in this domain have considered a fixed battery design. We argue that arrival of harvesting enabled sensors necessitates rethink of topology control. The objective of topology control in this context should not be to minimize the spent energy and maintain a reduced topology, but to maximize fault tolerance in the network and increase the sensing coverage region. In this work, we first describe a taxonomy of existing topology control schemes and analyze the impact of reduced topology over fault tolerance and sensing coverage. We then describe the necessity of new design parameters in the presence of harvest-able ambient energy. We also outline guiding principles for designing a harvesting enabled topology control scheme. To cater for whether such a scheme is feasible or not, an insight is also provided onto the solar energy availability from solar radiations for near perpetual operation—as an example of available ambient energy. Based on the insight gained from the solar radiations availability, we explain why new design parameters are required for performance measurement of harvesting enabled sensors. The mathematical and empirical findings reveal that the topology control strategies, which do not take into account harvesting opportunity, are unable to provide better results in terms of fault tolerance and sensing coverage.

A Cycle-based Clustering Algorithm for Wireless Sensor Networks

In energy constrained wireless sensor networks, it is important that a routing protocol provides network redundancy and reliability at a minimum energy consumption cost. To satisfy these conflicting constraints, wireless sensor networks (WSN) routing protocols generally employ a clustering algorithm in which the entire network does not have to be active at all times. In this paper, we propose a novel graph-theoretic clustering algorithm that exploits cycles in a connected and undirected WSN graph to provide redundancy and reliability in an energy efficient manner. The proposed algorithm also facilitates cluster head rotation for load distribution, thereby extending the network lifetime. Our performance evaluation shows that the proposed algorithm performs better than existing graph- theoretic clustering algorithms.

An energy-efficient link layer protocol for reliable transmission over wireless networks

In multihop wireless networks, hop-by-hop reliability is generally achieved through positive acknowledgments at the MAC layer. However, positive acknowledgments introduce significant energy inefficiencies on battery-constrained devices. This inefficiency becomes particularly significant on high error rate channels. We propose to reduce the energy consumption during retransmissions using a novel protocol that localizes bit-errors at the MAC layer. The proposed protocol, referred to as Selective Retransmission using Virtual Fragmentation (SRVF), requires simple modifications to the positive-ACK-based reliability mechanism but provides substantial improvements in energy efficiency. The main premise of the protocol is to localize bit-errors by performing partial checksums on disjoint parts or virtual fragments of a packet. In case of error, only the corrupted virtual fragments are retransmitted. We develop stochastic models of the Simple Positive-ACK-based reliability, the previously-proposed Packet Length Optimization (PLO) protocol, and the SRVF protocol operating over an arbitrary-order Markov wireless channel. Our analytical models show that SRVF provides significant theoretical improvements in energy efficiency over existing protocols. We then use bit-error traces collected over different real networks to empirically compare the proposed and existing protocols. These experimental results further substantiate that SRVF provides considerably better energy efficiency than Simple Positive-ACK and Packet Length Optimization protocols.

SRVF: An Energy-Efficient Link Layer Protocol for Reliable Transmission over Wireless Sensor Networks

The 802.15.4 WSN standard provides optional reliability through positive acknowledgments. Since positive-ACKs are not designed for energy efficiency, there is significant room for improvement in the energy usage of reliable 802.15.4. In this paper, we propose a new reliable link layer protocol, referred to as the Selective Retransmission using Virtual Fragmentation (SRVF) protocol. SRVF requires simple modifications to reliable 802.15.4, but provides substantial improvements in energy efficiency. The main premise of the proposed protocol is to localize bit-errors by performing partial checksums on disjoint parts or virtual fragments of a packet. In case of error, only the corrupted virtual fragments are retransmitted. We analytically model reliable 802.15.4 and SRVF as Markov chains operating over an arbitrary-order Markov wireless channel, and show that SRVF provides significant theoretical improvements over reliable 802.15.4. We then use bit-error traces collected over a real sensor network testbed to experimentally evaluate the two reliable protocols. These experimental results show that SRVF has consistently and considerably better energy efficiency than the reliable 802.15.4.

TRW: An energy storage capacity model for energy harvesting sensors in wireless sensor networks

Energy provisioning trend in Wireless Sensor Networks (WSNs) is shifted towards alternate sources by utilizing available ambient energy, of which solar irradiance harvesting is considered a viable alternative to fixed batteries. However, the energy storage buffer for harvested solar energy should be adaptive to the sporadic nature of the diurnal solar radiation availability. We believe that the typical fixed battery models no longer apply in harvesting enabled sensors. Therefore, we propose a random walk based stochastic model namely; Trinomial Random Walk (TRW) model for the storage capacity of harvesting enabled sensors. We then apply the proposed model on a comprehensive solar radiation data set of four different locations around the globe. Our performance evaluation demonstrates that the proposed model better analyze the sporadic nature of the diurnal solar radiation availability for estimating the required storage capacity. We further investigate an optimal power consumption value for a given energy store size, such that the utilization of harvested energy is maximized and the probability of energy depletion is minimized. For a given energy harvesting scenario, our model better approximates the optimal load with probability of up to a maximum of 98%, compared to a maximum of 37% for the binomial random walk model.

Meta-simulation of large WSN on multi-core computers

With the advances in wireless communications large scale Wireless Sensor Networks (WSN) are emerging with many applications. These networks are deployed to serve single objective application, with high optimization requirements such as performance enhancement and power saving. Application specific optimization is achieved using formal models and evaluation based simulations of distributed algorithms (DA) controlling such networks. The WSN design problem is of high complexity, and requires robust methodologies, including simulation support. Although we know several works on WSN simulation, these solutions fail to match requirements on a whole set of desirable criteria: scalability, flexibility, concurrent execution and performance. We present a model based approach of WSN application specification separating network organization from behaviors, allowing them to vary independently. Through this approach, network description can be achieved with high level tools independently from the programming syntax. We have specified and simulated number of WSN protocols with varying objectives and semantics using a time-driven execution model incorporated in the proposed meta-simulator. The empirical analysis has revealed flexibility, scalability and performance. The tool flow targets an Occam compiler producing efficient multi-threaded binaries. We expect the final flow of this project to enable sensor code production out of the simulated specification.

On the complexity of average path length for biological networks and patterns

Path length calculation is a frequent requirement in studies related to graph theoretic problems such as genetics. Standard method to calculate average path length (APL) of a graph requires traversing all nodes in the graph repeatedly, which is computationally expensive for graphs containing large number of nodes. We propose a novel method to calculate APL for graphs commonly required in the studies of genetics. The proposed method is computationally less expensive and less time-consuming compared to standard method.