Harsha Chenji

Toward Accurate Mobile Sensor Network Localization in Noisy Environments

The node localization problem in mobile sensor networks has received significant attention. Recently, particle filters adapted from robotics have produced good localization accuracies in conventional settings. In spite of these successes, state-of-the-art solutions suffer significantly when used in challenging indoor and mobile environments characterized by a high degree of radio signal irregularity. New solutions are needed to address these challenges. We propose a fuzzy logic-based approach for mobile node localization in challenging environments. Localization is formulated as a fuzzy multilateration problem. For sparse networks with few available anchors, we propose a fuzzy grid-prediction scheme. The fuzzy logic-based localization scheme is implemented in a simulator and compared to state-of-the-art solutions. Extensive simulation results demonstrate improvements in the localization accuracy from 20 to 40 percent when the radio irregularity is high. A hardware implementation running on Epic motes and transported by iRobot mobile hosts confirms simulation results and extends them to the real world.

On Modeling the Coexistence of 802.11 and 802.15.4 Networks for Performance Tuning

The explosion in the number of 802.11 and 802.15.4 deployments is exacerbating the coexistence problem, which has been reported in the literature to cause significant performance degradation in co-located networks employing the two different wireless standards. The wireless coexistence problem has, thus far, been studied primarily using hardware, due to the lack of analytical results and good wireless coexistence simulators. This paper presents the first analytical model for coexisting 802.11 and 802.15.4 networks. We derive analytically, using Markov chains, the normalized saturation throughput under coexistence. Additionally, we propose a performance tuning method that ensures QoS and a distributed Nash-equilibrium-based method that ensures fairness. We validate our model and the tuning methods using a coexistence simulator previously developed and presented by the authors. We demonstrate that our model has a low average error smaller than 10%.

Enhancement of wireless bandwidth utilization through user's QoE

Quality of Experience (QoE) measures a users satisfaction with a service delivery. However QoE is a very subjective measure and is context dependent, making it difficult for a service provider to estimate and optimize users QoE. In this paper, we look at how the provider can maximize QoE by optimizing wireless bandwidth allocation, especially for mobile cloud applications. The multi-stimuli version of the “IQX” hypothesis is used to model the QoE of a user, and this model is used in formulation of a nonlinear optimization problem, which is solved using NSGA-II. Simulations using realistic parameters based on 802.11n demonstrate a reduction in the required bandwidth by as much as 33% (i.e., more users can be accommodated by the system), while maintaining the same level of QoE. Our evolutionary-algorithm-based approach is able to discover the optimal bandwidth allocation. The problem of equalizing user QoE is explored and a tradeoff between QoE and fairness is studied, while being characterized using a Pareto front.

Pareto optimal cross layer lifetime optimization for Disaster Response Networks

Disaster Response Networks (DRNs) are designed to assist first responders during the recovery period following a large scale disaster. The system lifetime of deployed DRNs is critical to successful recovery, as are performance metrics such as packet delivery delay. In this paper we investigate the Pareto front between system performance and system energy consumption in such DRNs. The latter is further reduced compared to state of art methods by accepting the least possible performance penalty as a tradeoff. We observe that not all nodes in the network may consume or produce data; such relay nodes can be excluded from the routing process to save energy, but at the cost of decreased system performance. The problem is formulated mathematically using Raven as the underlying routing protocol. The Nondominated Sorting Genetic Algorithm II (NSGA-II) is used to obtain the Pareto-optimal points, and the DRN is made to operate at these points. Extensive performance evaluations demonstrate that a 162 minute increase in system lifetime is possible for a 61 minute increase in the packet delivery delay, while the packet delivery ratio remains almost constant.

Raven: Energy aware QoS control for DRNs

Disaster Response Networks (DRNs) are disruption tolerant networks designed to deliver mission critical data during disaster recovery, while operating with limited energy resources. While Quality of Service is desired, it is difficult to offer guarantees because of the unpredictable nature of mobility in such DRNs. The variance of the packet delivery delay (PDV, more commonly called jitter), an important QoS metric which in DRNs is measured in tens of minutes instead of milliseconds, has not been sufficiently addressed in recent research. Smartphones used by first responders generate large data workloads, causing the PDV to further degrade. Reducing packet replication at these workloads will lower energy consumption, but reduces the packet delivery ratio (PDR). The complex interplay between these QoS metrics remains unclear, making their control difficult. We present Raven, a routing protocol for DRNs that offers control over QoS, especially the PDV. Stochastic graph theory which deals with probabilistic edge weights having a mean and variance is used to model mobility in the disaster area. A stochastic version of the K-Shortest Paths algorithm routes data over multiple paths simultaneously. Raven has been thoroughly evaluated in simulation using realistic settings. The dynamics between performance and energy consumption is analyzed mathematically, and its control is demonstrated.

Optimal Multicasting in Hybrid RF/FSO DTNs

The multi-copy routing paradigm in Delay Tolerant Networks (DTNs) implies that increasing contact bandwidth leads to a decrease in data delivery delay and an improvement in throughput. With Hybrid Radio Frequency/Free Space Optical (RF/FSO) PHY layers, the high data rate FSO links can be used to increase the contact bandwidth. However, due to the highly directional nature of FSO links, broadcasting is difficult. A naive broadcast strategy where the beam divergence angle is increased to include many nodes in the broadcast set results in low data rate, and does not always result in the minimum achievable delay. In this work we develop an optimal multicast algorithm for hybrid RF/FSO networks. We show that the problem is an abstraction of the minimum weight set cover problem which is known to be NP- hard. A computationally cheap greedy local optimum heuristic is proposed. A comprehensive evaluation using delay, throughput and computation time as metrics is performed using various solutions. These extensive evaluations show that our solution outperforms both naive broadcast and multiple unicast, taking 95% less time as compared to the exact algorithm, while providing comparable performance.

Low complexity QoE-aware bandwidth allocation for wireless content delivery

Bandwidth allocation in spectrum-congested wire- less content delivery networks should be performed based on the users Quality of Experience (QoE). The relationship between QoE and network QoS is context- and user-dependent. We show that modeling the users QoE introduces additional complexity to the bandwidth allocation problem. While recent research has proposed various ways in which complexity can be reduced, we have observed that the optimality (w.r.t. QoE) of the system is also reduced along with complexity. In this paper, the tradeoff between complexity and optimality is investigated and methods to control the tradeoff are proposed. A bandwidth allocation scheme for three different system objectives, including fairness, is formulated.

A network-centric model of situational awareness

In a wireless ad hoc multimedia network, how does the Quality of Experience (QoE) of the user affect the level of Situational Awareness (SA)? Is maximum QoE necessary for high SA? In this empirical study, we propose a novel measurement approach to quantify SA based on the QoE of the user. The relationship between QoE and network Quality of Service (QoS) metrics such as delay and packet loss is well known. Therefore, quantifying the SA-QoE-QoS relationship will help the network operator to ensure a high level of SA when the network is under attack, through parsimonious allocation of network resources such as spectrum and power. We first define SA metrics in four contexts: Surroundings awareness, Target awareness, Location awareness, and Responsiveness (SETLR model). Next, we design an experiment and define an objective expression for each SETLR metric. We mathematically formulate SA as a function of QoE, using real data, and show that this relationship is logistic in nature. This new utility function for measuring SA can now be used in network optimization techniques to avoid over-provisioning. Finally, we observe that maximum QoE is in fact not necessary to ensure high SA; a Mean Opinion Score of just 2–3 is necessary in our scenario.

Overcoming alignment delay in RF+FSO networks

The use of highly directional antennae in wireless networks has been shown to increase network capacity. As the beamwidth decreases, near perfect alignment is required to achieve these capacity gains. This becomes particularly challenging in mobile adhoc networks, leading to high alignment delay. In this paper, we explore ways of mitigating alignment delay in practical delay tolerant networks (DTNs) where each node has both a radio frequency (RF) control and a free space optical (FSO) data channel. We show that overcoming alignment delay while multicasting data during contact opportunities is an abstraction of the minimum weighted set cover problem. An optimal multicast scheme is implemented in a DTN simulator over a new session-based MAC protocol. Thorough performance evaluation demonstrates that we can compensate for fixed alignment delay, paving the way for high capacity DTNs.

Multicast techniques for hybrid RF/FSO DTNs

Increasing the contact bandwidth in delay tolerant networks (DTNs) via multicopy routing leads to a decrease in data delivery delay and an improvement in throughput. In DTNs, in which nodes have both radio frequency (RF) and free space optical (FSO) PHY layers, contact bandwidth can be increased by using the FSO PHY as the data channel and performing multicasting. As we show in this paper, due to the highly directional nature of FSO, a naïve broadcast strategy where the beam divergence includes all nodes in the broadcast set, it does not always result in the minimization of data delivery delay and the maximization of delivery probability. To this end, we develop multicast strategies for hybrid RF/FSO DTNs via an emulation of static conditions in mobile DTNs in which RF is primarily used for control. We show that the optimal multicast problem in static environments is an abstraction of the minimum weighted set cover problem, which is known to be NP-hard. To save on computation time, we propose a greedy local optimum heuristic. Performance of the various multicast techniques is comprehensively evaluated in a DTN simulator, using the Epidemic routing protocol. These evaluations show that our computationally cheap solution yields results identical to optimal while not compromising the performance of the DTN.