Performance Evaluation of OBS Networks with INI Signaling Technique

In this paper, we evaluate the performance of a burst retransmission method for an optical burst switched network with intermediate-node-initiation (INI) signaling technique. The proposed method tries to reduce the burst contention probability at the intermediate core nodes. We develop an analytical model to get the burst contention probability and burst loss probability for an optical burst switched network with intermediate-node-initiation signaling technique. The proposed method uses the optical burst retransmission method. We simulate the performance of the optical burst retransmission. Simulation results show that at low traffic loads the loss probability is low compared to the conventional burst retransmission in the OBS network. Result also show that the retransmission method for OBS network with intermediate-node-initiation signaling technique significantly reduces the burst loss probability.

On interference alignment for symmetrically connected interference networks with line of sight channels at finite powers

In this work, interference alignment for a class of Gaussian interference networks with general message demands, having line of sight (LOS) channels, at finite powers is considered. We assume that each transmitter has one independent message to be transmitted and the propagation delays are uniformly distributed between 0 and (L - 1) (L >; 0). If receiver-j, j ∈{1,2,..., J}, requires the message of transmitter-i, i ∈ {1, 2, ..., K}, we say (i, j) belongs to a connection. A class of interference networks called the symmetrically connected interference network is defined as a network where, the number of connections required at each transmitter-i is equal to ct for all i and the number of connections required at each receiver-j is equal to cr for all j, for some fixed positive integers ct and cr. For such networks with a LOS channel between every transmitter and every receiver, we show that an expected sum-spectral efficiency (in bits/sec/Hz) of at least K/(e+c1-1)(ct+1) (ct/ct+1)ct log2 (1+min(i, j)∈c|hi, j|2 P/WN0) can be achieved as the number of transmitters and receivers tend to infinity, i.e., K, J →∞ where, C denotes the set of all connections, hij is the channel gain between transmitter-i and receiver-j, P is the average power constraint at each transmitter, W is the bandwidth and N0 W is the variance of Gaussian noise at each receiver. This means that, for an LOS symmetrically connected interference network, at any finite power, the total spectral efficiency can grow linearly with K as K, J →∞. This is achieved by extending the time domain interference alignment scheme proposed by Grokop et al. for the k-user Gaussian interference channel to interference networks.

Game theoretic analysis of collusions in nonneutral networks

This paper studies the impact of exclusive contracts between a content provider (CP) and an internet service provider (ISP) in a nonneutral network. We consider a simple linear demand function for the CPs. We studywhen an exclusive contract is benefcial to the colluding pair and evaluate its impact on the noncolluding players at equilibrium. For the case of two CPs and one ISP we show that collusion may not always be benefcial. We derive an explicit condition in terms of the advertisement revenues of the CPs that tells when a collusion is proftable to the colluding entities.

Performance analysis of beacon-less IEEE 802.15.4 multi-hop networks

We develop an approximate analytical technique for evaluating the performance of multi-hop networks based on beacon-less CSMA/CA as standardised in IEEE 802.15.4, a popular standard for wireless sensor networks. The network comprises sensor nodes, which generate measurement packets, and relay nodes which only forward packets. We consider a detailed stochastic process at each node, and analyse this process taking into account the interaction with neighbouring nodes via certain unknown variables (e.g., channel sensing rates, collision probabilities, etc.). By coupling these analyses of the various nodes, we obtain fixed point equations that can be solved numerically to obtain the unknown variables, thereby yielding approximations of time average performance measures, such as packet discard probabilities and average queueing delays. Different analyses arise for networks with no hidden nodes and networks with hidden nodes. We apply this approach to the performance analysis of tree networks rooted at a data sink. Finally, we provide a validation of our analysis technique against simulations.

Optimal Forwarding in Delay-Tolerant Networks With Multiple Destinations

We study the tradeoff between delivery delay and energy consumption in a delay-tolerant network in which a message (or a file) has to be delivered to each of several destinations by epidemic relaying. In addition to the destinations, there are several other nodes in the network that can assist in relaying the message. We first assume that, at every instant, all the nodes know the number of relays carrying the message and the number of destinations that have received the message. We formulate the problem as a controlled continuous-time Markov chain and derive the optimal closed-loop control (i.e., forwarding policy). However, in practice, the intermittent connectivity in the network implies that the nodes may not have the required perfect knowledge of the system state. To address this issue, we obtain an ordinary differential equation (ODE) (i.e., a deterministic fluid) approximation for the optimally controlled Markov chain. This fluid approximation also yields an asymptotically optimal open-loop policy. Finally, we evaluate the performance of the deterministic policy over finite networks. Numerical results show that this policy performs close to the optimal closed-loop policy.

Performance Analysis of a Cooperative MAC Protocol of Wireless Ad Hoc Networks

Different medium access control (MAC) layer protocols, for example, IEEE 802.11 series and others are used in wireless local area networks. They have limitation in handling bulk data transfer applications, like video-on-demand, videoconference, etc. To avoid this problem a cooperative MAC protocol environment has been introduced, which enables the MAC protocol of a node to use its nearby nodes MAC protocol as and when required. We have found on various occasions that specified cooperative MAC establishes cooperative transmissions to send the specified data to the destination. In this paper we propose cooperative MAC priority (CoopMACPri) protocol which exploits the advantages of priority value given by the upper layers for selection of different paths to nodes running heterogeneous applications in a wireless ad hoc network environment. The CoopMACPri protocol improves the system throughput and minimizes energy consumption. Using a Markov chain model, we developed a model to analyse the performance of CoopMACPri protocol; and also derived closed-form expression of saturated system throughput and energy consumption. Performance evaluations validate the accuracy of the theoretical analysis, and also show that the performance of CoopMACPri protocol varies with the number of nodes. We observed that the simulation results and analysis reflects the effectiveness of the proposed protocol as per the specifications.

Precoding-Based Network Alignment Using Transform Approach for Acyclic Networks With Delay

The algebraic formulation for linear network coding in acyclic networks with the links having integer delay is well known. Based on this formulation, for a given set of connections over an arbitrary acyclic network with integer delay assumed for the links, the output symbols at the sink nodes, at any given time instant, is a F(p)m-linear combination of the input symbols across different generations, where F(p)m denotes the field over which the network operates (p is prime and m is a positive integer). We use finite-field discrete Fourier transform to convert the output symbols at the sink nodes, at any given time instant, into a F(p)m-linear combination of the input symbols generated during the same generation without making use of memory at the intermediate nodes. We call this as transforming the acyclic network with delay into n-instantaneous networks (n is sufficiently large). We show that under certain conditions, there exists a network code satisfying sink demands in the usual (nontransform) approach if and only if there exists a network code satisfying sink demands in the transform approach. When the zero-interference conditions are not satisfied, we propose three precoding-based network alignment (PBNA) schemes for three-source three-destination multiple unicast network with delays (3-S 3-D MUN-D) termed as PBNA using transform approach and time-invariant local encoding coefficients (LECs), PBNA using time-varying LECs, and PBNA using transform approach and block time-varying LECs. We derive sets of necessary and sufficient conditions under which throughputs close to n' + 1/2n' + 1, n'/2n' + 1, and n'/2n' + 1 are achieved for the three source-destination pairs in a 3-S 3-D MUN-D employing PBNA using transform approach and time-invariant LECs, and PBNA using transform approach and block time-varying LECs, where n' is a positive integer. For PBNA using time-varying LECs, we obtain a sufficient condition under which a throughput demand of n(1)/n, n(2)/n, and n(3)/n can be met for the three source-destination pairs in a 3-S 3-D MUN-D, where n(1), n(2), and n(3) are positive integers less than or equal to the positive integer n. This condition is also necessary when n(1) + n(3) = n(1) + n(2) = n where n(1) >= n(2) >= n(3).

Co-Evolution of Content Spread and Popularity in Mobile Opportunistic Networks

We consider a setting in which a single item of content is disseminated in a population of mobile nodes by opportunistic copying when pairs of nodes come in radio contact. The nodes in the population may either be interested in receiving the content (referred to as destinations) or not yet interested in receiving the content (referred to as relays). We consider a model for the evolution of popularity, the process by which relays get converted into destinations. A key contribution of our work is to model and study the joint evolution of content popularity and its spread in the population. Copying the content to relay nodes is beneficial since they can help spread the content to destinations, and could themselves be converted into destinations. We derive a fluid limit for the joint evolution model and obtain optimal policies for copying to relay nodes in order to deliver content to a desired fraction of destinations, while limiting the fraction of relay nodes that get the content but never turn into destinations. We prove that a time-threshold policy is optimal for controlling the copying to relays, i.e., there is an optimal time-threshold up to which all opportunities for copying to relays are exploited, and after which relays are not copied to. We then utilize simulations and numerical evaluations to provide insights into the effects of various system parameters on the optimally controlled co-evolution model.

An Eigen Approach to Transmit Beamforming in Wireless Networks With Single Antenna Receivers

In this paper, we propose an eigen framework for transmit beamforming for single-hop and dual-hop network models with single antenna receivers. In cases where number of receivers is not more than three, the proposed Eigen approach is vastly superior in terms of ease of implementation and computational complexity compared with the existing convex-relaxation-based approaches. The essential premise is that the precoding problems can be posed as equivalent optimization problems of searching for an optimal vector in the joint numerical range of Hermitian matrices. We show that the latter problem has two convex approximations: the first one is a semi-definite program that yields a lower bound on the solution, and the second one is a linear matrix inequality that yields an upper bound on the solution. We study the performance of the proposed and existing techniques using numerical simulations.

Performance Analysis of Space-Shift Keying in Decode-and-Forward Multihop MIMO Networks

In this paper, space-shift keying (SSK) is considered for multihop multiple-input-multiple-output (MIMO) networks. In SSK, only one among n(s) = 2(m) available transmit antennas, chosen on the basis of m information bits, is activated during transmission. We consider two different systems of multihop co-operation, where each node has multiple antennas and employs SSK. In system I, a multihop diversity relaying scheme is considered. In system II, a multihop multibranch relaying scheme is considered. In both systems, we adopt decode-and-forward (DF) relaying, where each relay forwards the signal only when it correctly decodes. We analyze the end-to-end bit error rate (BER) and diversity order of both the systems with SSK. For binary SSK (n(s) = 2), our analytical BER expression is exact, and our numerical results show that the BERs evaluated through the analytical expression overlap with those obtained through Monte Carlo simulations. For nonbinary SSK (n(s) > 2), we derive an approximate BER expression, where the analytically evaluated BER results closely follow the simulated BER results. We show the comparison of the BERs of SSK and conventional phase-shift keying (PSK) and also show the instances where SSK outperforms PSK. We also present the diversity analyses for SSK in systems I and II, which predict the achievable diversity orders as a function of system parameters.

A Novel and Scalable LED Communication System

We describe our novel LED communication infrastructure and demonstrate its scalability across platforms. Our system achieves 50 kilo bits per second on very simple SoCs and scales to megabits bits per second rates on dual processor based mobile phone platforms.

Adaptive Sleep-Wake Control using Reinforcement Learning in Sensor Networks

The aim in this paper is to allocate the `sleep time' of the individual sensors in an intrusion detection application so that the energy consumption from the sensors is reduced, while keeping the tracking error to a minimum. We propose two novel reinforcement learning (RL) based algorithms that attempt to minimize a certain long-run average cost objective. Both our algorithms incorporate feature-based representations to handle the curse of dimensionality associated with the underlying partially-observable Markov decision process (POMDP). Further, the feature selection scheme used in our algorithms intelligently manages the energy cost and tracking cost factors, which in turn assists the search for the optimal sleeping policy. We also extend these algorithms to a setting where the intruder's mobility model is not known by incorporating a stochastic iterative scheme for estimating the mobility model. The simulation results on a synthetic 2-d network setting are encouraging.

Low Complexity Power and Scheduling Policies for Wireless Networks to Provide Quality of Service

We consider optimal power allocation policies for a single server, multiuser system. The power is consumed in transmission of data only. The transmission channel may experience multipath fading. We obtain very efficient, low computational complexity algorithms which minimize power and ensure stability of the data queues. We also obtain policies when the users may have mean delay constraints. If the power required is a linear function of rate then we exploit linearity and obtain linear programs with low complexity.

Optimal power allocation for protective jamming in wireless networks: A flow based model

We address the problem of passive eavesdroppers in multi-hop wireless networks using the technique of friendly jamming. The network is assumed to employ Decode and Forward (DF) relaying. Assuming the availability of perfect channel state information (CSI) of legitimate nodes and eavesdroppers, we consider a scheduling and power allocation (PA) problem for a multiple-source multiple-sink scenario so that eavesdroppers are jammed, and source-destination throughput targets are met while minimizing the overall transmitted power. We propose activation sets (AS-es) for scheduling, and formulate an optimization problem for PA. Several methods for finding AS-es are discussed and compared. We present an approximate linear program for the original nonlinear, non-convex PA optimization problem, and argue that under certain conditions, both the formulations produce identical results. In the absence of eavesdroppers' CSI, we utilize the notion of Vulnerability Region (VR), and formulate an optimization problem with the objective of minimizing the VR. Our results show that the proposed solution can achieve power-efficient operation while defeating eavesdroppers and achieving desired source-destination throughputs simultaneously. (C) 2015 Elsevier B.V. All rights reserved.

Relay Selection with Channel Probing in Sleep-Wake Cycling Wireless Sensor Networks

In geographical forwarding of packets in a large wireless sensor network (WSN) with sleep-wake cycling nodes, we are interested in the local decision problem faced by a node that has ``custody'' of a packet and has to choose one among a set of next-hop relay nodes to forward the packet toward the sink. Each relay is associated with a ``reward'' that summarizes the benefit of forwarding the packet through that relay. We seek a solution to this local problem, the idea being that such a solution, if adopted by every node, could provide a reasonable heuristic for the end-to-end forwarding problem. Toward this end, we propose a local relay selection problem consisting of a forwarding node and a collection of relay nodes, with the relays waking up sequentially at random times. At each relay wake-up instant, the forwarder can choose to probe a relay to learn its reward value, based on which the forwarder can then decide whether to stop (and forward its packet to the chosen relay) or to continue to wait for further relays to wake up. The forwarder's objective is to select a relay so as to minimize a combination of waiting delay, reward, and probing cost. The local decision problem can be considered as a variant of the asset selling problem studied in the operations research literature. We formulate the local problem as a Markov decision process (MDP) and characterize the solution in terms of stopping sets and probing sets. We provide results illustrating the structure of the stopping sets, namely, the (lower bound) threshold and the stage independence properties. Regarding the probing sets, we make an interesting conjecture that these sets are characterized by upper bounds. Through simulation experiments, we provide valuable insights into the performance of the optimal local forwarding and its use as an end-to-end forwarding heuristic.