Single Source-destination Pair Research Articles

Minimizing age of information under arbitrary arrival model with arbitrary packet size

We consider a single source–destination pair, where information updates (in short, updates) arrive at the source at arbitrary time instants. For each update, its size, i.e. the service time required for complete transmission to the destination, is also arbitrary. At any time, the source may choose which update to transmit, while incurring transmission cost that is proportional to the duration of transmission. We consider the age of information (AoI) metric that quantifies the staleness of the update (information) at the destination. At any time, AoI is equal to the difference between the current time, and the arrival time of the latest update (at the source) that has been completely transmitted (to the destination). The goal is to find a causal (i.e. online) scheduling policy that minimizes the sum of the AoI and the transmission cost, where the possible decisions at any time are (i) whether to preempt the update under transmission upon arrival of a new update, and (ii) if no update is under transmission, then choose which update to transmit (among the available updates). In this paper, we propose a causal policy called SRPT+ that at each time, (i) preempts the update under transmission if a new update arrives with a smaller size (compared to the remaining size of the update under transmission), and (ii) if no update is under transmission, then from the set of available updates with size less than a threshold (which is a function of the transmission cost and the current AoI), begins to transmit the update for which the ratio of the reduction in AoI upon complete transmission (if not preempted in future) and the remaining size, is maximum. We characterize the performance of SRPT+ using a metric called the competitive ratio, i.e. the ratio of the cost of causal policy and the cost of an optimal offline policy (that knows the entire input in advance), maximized over all possible inputs. We show that the competitive ratio of SRPT+ is at most 5. In the special case when there is no transmission cost, we further show that the competitive ratio of SRPT+ is at most 3.

Efficient single-pair all-shortest-path query processing for massive dynamic networks

The single-pair all-shortest-path problem is to find all possible shortest paths, given a single source-destination pair in a graph. Due to the lack of efficient algorithms for single-pair all-shortest-path problem, many applications used diverse types of modifications to the existing shortest-path algorithms such as Dijkstra’s algorithm. Such approaches can facilitate the analysis of medium-sized static networks, but the heavy computational cost impedes their use for massive and dynamic real-world networks. In this paper, we present a novel single-pair all-shortest-path algorithm, which performs well on massive networks as well as dynamic networks. The efficiency of our algorithm stems from novel 2-hop label-based query processing on large-size networks. For dynamic networks, we also demonstrate how to incrementally maintain all shortest paths in 2-hop labels, which allows our algorithm to handle the topological changes of dynamic networks such as insertion or deletion of edges. We carried out experiments on real-world large datasets, and the results confirms the effectiveness of our algorithms for the single-pair all-shortest-path computation and the incremental maintenance of 2-hop labels.

AoI-Optimal Joint Sampling and Updating for Wireless Powered Communication Systems

This paper characterizes the structure of the Age of Information (AoI)-optimal policy in wireless powered communication systems while accounting for the time and energy costs of generating status updates at the source nodes. In particular, for a single source-destination pair in which a radio frequency (RF)-powered source sends status updates about some physical process to a destination node, we minimize the long-term average AoI at the destination node. The problem is modeled as an average cost Markov Decision Process (MDP) in which, the generation times of status updates at the source, the transmissions of status updates from the source to the destination, and the wireless energy transfer (WET) are jointly optimized. After proving the monotonicity property of the value function associated with the MDP, we analytically demonstrate that the AoI-optimal policy has a threshold-based structure w.r.t. the state variables. Our numerical results verify the analytical findings and reveal the impact of state variables on the structure of the AoI-optimal policy. Our results also demonstrate the impact of system design parameters on the optimal achievable average AoI as well as the superiority of our proposed joint sampling and updating policy w.r.t. the generate-at-will policy.

Tracking routes in communication networks

The minimum tracking set problem is an optimization problem that deals with monitoring communication paths that can be used for exchanging point-to-point messages using as few tracking devices as possible. More precisely, a tracking set of a given graph G and a set of source-destination pairs of vertices is a subset T of vertices of G such that the vertices in T traversed by any source-destination shortest path P uniquely identify P. The minimum tracking set problem has been introduced in Banik et al., CIAC (2017) [1] for the case of a single source-destination pair. There, the authors show that the problem is APX-hard and that it can be 2-approximated for the class of planar graphs, even though no hardness result is known for this case. In this paper we focus on the case of multiple source-destination pairs and we present the first O˜(n)-approximation algorithm for general graphs. Moreover, we prove that the problem remains NP-hard even for cubic planar graphs and all pairs S×D, where S and D are the sets of sources and destinations, respectively. Finally, for the case of a single source-destination pair, we design an (exact) FPT algorithm w.r.t. the maximum number of vertices at the same distance from the source.

On maximizing information reliability in wireless powered cooperative networks

Unpredictable nature of fading channels and difficulty in tracking channel state information pose major challenge in wireless energy harvesting communication system design. In this work, we address relay selection problem for wireless powered communication networks, where the relays harvest energy from the source radio frequency signals. A single source–destination pair is considered without a direct link. The connecting relay nodes are equipped with storage batteries of infinite size. We assume that the channel state information (CSI) on the source–relay link is available at the relay nodes. Depending on the availability of the CSI on the relay–destination link at the relay node, we propose two relay selection schemes and evaluate their outage probability. Availability of the CSI at the relay node on the relay–destination link considerably improves the performance due to additional flexibility in the relay selection mechanism. Due to absence of CSI throughout the network at the time of transmission path selection, the analysis of the problem is not tractable. Therefore, we relax our assumptions on availability of CSI and closed-form expressions of the outage probability as a function of the amount of the available harvested energy are derived for both CSI availability cases. Finally, we numerically quantify the performance for the proposed schemes and compare the outage probability for fixed and equal number of wireless powered forwarding relays.

On the Age of Information in Wireless Networks Using Rateless Codes

The information freshness, quantified by the emerging idea of Age of Information (AoI), has recently received widespread attentions from both academia and industry. However, most prior works on AoI considered a single source-destination pair and provided the performance analysis merely through queueing-theoretic models, which do not lend themselves to the analysis of large-scale wireless networks. This paper focuses on the AoI analysis in a large-scale setting using random spatial models in stochastic geometry. Specifically, we first adopt rateless coding for packet delivery to improve the transmission reliability while reducing the transmission delay. Then, to quantify the enhancement of the information freshness by rateless coding, we derive the average peak age of information (PAoI) in Poisson bipolar and cellular networks, which characterizes the maximum value of AoI immediately before an update packet is received accounting for the spatial variation of network nodes and temporal dynamics of service packets. With these results, we further give the conditions that make the average PAoI to be finite in each type of the network. Numerical results show the significant benefits of rateless codes relative to the commonly used fixed-rate codes in terms of the PAoI and the feasible region of system parameters such as the traffic arrival rate, transmit probability, etc., in Poisson bipolar and cellular networks.

ESLR - Energy Based Stable Link Routing in Mobile Adhoc Networks

Mobile ad hoc network (MANET) comprises of highly dynamic mobile nodes where reliable and stable path routing is a major issue which affects uninterrupted communication. There are so many stable routing protocols are developed as a promising solution. Nevertheless, while developing stable routes energy based a vital role. This paper proposed a novel energy based stable link routing (ESLR) protocol that chooses high energy routes to create stable link communication. In our proposed technique, traffic manager elected to control the entire operation of the network. For that it observes all the activities of every single node that participating in the communication. When a node wants to send packets, the traffic manager chooses routes between the source-destination pair based on energy i.e. next forwarding link is created between the highest energy nodes. Thereby the stable links are created which can perform long-lasting communication. The proposed protocol has minimum of five routes for every single source-destination pair. So, without any delay next alternate path is selected if anyone of the intermediate node reaches its minimum energy. The simulation is performed to observe the performance of the proposed ESLR protocol. In experimental results, the observed performance of the proposed technique is compared with the existing AODVM and LSMRP protocols in terms of routing control overhead, number of route discovery and average end-to-end delay and the results are plotted.

Dynamic Atomic Congestion Games with Seasonal Flows

We propose a model of discrete time dynamic congestion games with atomic players and a single source-destination pair. The latencies of edges are composed of free-flow transit times and possible queuing time due to capacity constraints. We give a precise description of the dynamics induced by the individual strategies of players and of the corresponding costs, either when the traffic is controlled by a planner, or when players act selfishly. In parallel networks, optimal and equilibrium behavior eventually coincide, but the selfish behavior of the initial players has consequences that cannot be undone and are paid by all future generations. In more general topologies, our main contributions are threefold. First, we illustrate a new dynamic version of Braess paradox: the presence of initial queues in the network may decrease the long-run costs in equilibrium. This paradox can arise in networks for which no Braess paradox was previously known. Second, we show that equilibria are not unique and can induce very different long-run costs. In particular, we give a sequence of networks such that the price of stability is equal to 1, and the price of anarchy is equal to n − 1, where n is the number of vertices. Third, we propose an extension to model seasonalities by assuming that departure flows fluctuate periodically over time. We introduce a measure that captures the queues induced by periodicity of inflows. For optimal and equilibrium flows in parallel networks this measure is the increase in cost compared to uniform departures. The electronic companion is available at https://doi.org/10.1287/opre.2017.1683 .

Enhancing Network Robustness via Shielding

We consider shielding critical links to enhance the robustness of a network, in which shielded links are resilient to failures. We first study the problem of increasing network connectivity by shielding links that belong to small cuts of a network, which improves the network reliability under random link failures. We then focus on the problem of shielding links to guarantee network connectivity under geographical and general failure models. We develop a mixed integer linear program (MILP) to obtain the minimum cost shielding to guarantee the connectivity of a single source–destination pair under a general failure model, and exploit geometric properties to decompose the shielding problem under a geographical failure model. We extend our MILP formulation to guarantee the connectivity of the entire network, and use Benders decomposition to significantly reduce the running time. We also apply simulated annealing to obtain near-optimal solutions in much shorter time. Finally, we extend the algorithms to guarantee partial network connectivity, and observe significant reduction in the shielding cost, especially when the geographical failure region is small.

Diagonal Amplifying Matrix Design in Multihop Distributed Relay Networks

In this paper, we study a multihop distributed relay network consisting of a single source–destination pair and multiple nonregenerative single-antenna relay nodes, which are arranged in different layers. Due to the distributed deployment, the amplifying matrix of the relay nodes at each layer has to be a diagonal matrix. We adopt a layer-by-layer approach to compute the relay amplifying matrices with the objective of maximizing the end-to-end transmission rate. The amplifying matrix of each layer is derived from a per-layer sum-rate maximization problem. When there is only one receiving node at the direct forward layer, the nonconvex per-layer sum-rate maximization problem is equivalently converted into a convex quadratically constrained quadratic program and could be efficiently solved. When there are multiple receiving nodes at the direct forward layer, the nonconvex per-layer sum-rate maximization problem is more challenging. We then transform it into a difference-of-convex program and design iterative convex programing to yield an approximate solution. The analysis shows that the proposed iterative algorithm will converge to local optima of the per-layer sum-rate maximization problem. Simulation results confirm that the proposed scheme outperforms the existing works in terms of the end-to-end transmission rate and is more effective in suppressing noise propagation.

Dynamic Decode‐and‐Forward Relaying with Partial CSIT and Optimal Time Allocation

A Dynamic decode-and-forward (DDF) relaying protocol with partial Channel state information at the transmitter (CSIT) for a three-node half-duplex single-antenna network, which consists of a single source destination pair and a relay, is proposed. A Diversity multiplexing trade off (DMT) analysis is presented, in which the DMT of the proposed protocol is derived in a closed form and an adaptive time allocation strategy is also developed to achieve the optimal performance. It is shown that time allocation with partial CSIT significantly improves the achievable DMT for DDF relaying. Moreover, unlike the existing DDF protocol with CSIT, which is performed with the assumption of long-term power constraint, the proposed protocol can be generalized to the practical scenarios where a strict short-term power constraint is often imposed on, due to the environmental safety and interference prevention.

Outage Performance Analysis of Imperfect-CSI-Based Selection Cooperation in Random Networks

Selection of relays is central to efficient utilization of cooperative diversity gains when multiple relays are available in the network. Such selection is generally based on some form of channel state information (CSI), which is always imperfect in practice. The effects of using imperfect CSI in a relay selection process have been generally considered in existing literature without the account for spatial distribution of relays, while current works on relay selection in random networks mainly assume perfect CSI. In this paper, we analyze the outage performance of a single source-destination pair communicating through a decode-and-forward relay, chosen from a Poisson point process (PPP) of candidate relays using perfect and imperfect CSI. We derive exact outage probability expressions for the selection cooperation strategy. Closed-form expressions are provided for special cases, and asymptotic analysis is conducted to highlight the highSNR system behavior.

Distributed Cooperative Topology Control for WANETs With Opportunistic Interference Cancelation

Cooperative communications has received tremendous interests in wireless systems. The communication performance of a single source-destination pair can be enhanced via the help of relays in traditional cooperative communications. Recent advances in interference cancelation (IC) can further enhance the performance of parallel cooperative transmissions between multiple source-destination pairs. Although some works have been done on cooperative communications, most existing works are focused on link-level physical-layer issues. Consequently, the potential benefits of cooperative communications on network-level upper layer issues, such as topology control, are largely ignored in existing works. In this paper, we study the impacts of cooperative communications, particularly IC-based cooperative communications, on topology control in wireless ad hoc networks (WANETs). We propose a distributed cooperative topology control scheme with opportunistic IC (COIC) to improve network capacity in WANETs by jointly considering both upper layer network capacity and physical-layer cooperative communications with IC. We show that the benefits brought by cooperative communications are opportunistic, which rely on network structures and channel conditions. These opportunistic advantages have significant impacts on network capacity, and our proposed COIC can effectively capture these opportunities to substantially improve network capacity.

An MMSE Strategy at Relays With Partial CSI for a Multi-Layer Relay Network

We consider a relay network with a single source-destination pair and multiple layers of relays between them. We assume that these layers sequentially relay the signal transmitted by the source to the destination. Unlike existing work, we also assume that the destination and all the forward layers present between the transmitting layer and the destination receive signals during every transmission phase. We optimally combine these signals, say μ of them, using a precoder at each relay layer for onward transmission. We obtain this precoding matrix by minimizing the mean-squared error (MSE) at the relays, and do not require channel-state-information (CSI) of the forward channels at the relays unlike existing systems that minimize MSE at the destination and require CSI of the forward channels at the relays. Our closed-form solution for this matrix is valid for any K number of layers, whereas minimizing MSE at the destination does not have closed-form solution for K > 1. For K > 1, we enhance an existing scheme to obtain a sub-optimal closed-form precoder solution and use it for comparison. We show using simulations that our scheme approaches the bit-error-rate (BER) performance of this scheme, when μ is increased, even with partial CSI.

Optimal Routing and Power Allocation for Wireless Networks with Imperfect Full-Duplex Nodes

The joint routing and power allocation problem in a wireless full-duplex network with imperfect interference cancellation and a single source destination pair is solved. Our simplified interference model focuses on the effects of full-duplex by including residual self-interference and one hop interference while other interfering signals are assumed to be negligible. First, the optimal power allocation for a fixed route is identified. Then a modification of Dijkstra's algorithm is used to find the joint route and power allocation to maximize throughput. Due to interference, the algorithm proposed has a non decomposable objective function; however, it is efficiently solved for every candidate route. Our solution in a full interference model, that does not ignore any interference, is at most a constant bound away from the optimal solution in the full interference model. Through simulations we evaluate several scenarios and show the behavior of the solution in both interference models.

Best and worst-case coverage problems for arbitrary paths in wireless sensor networks

The path-based coverage of a wireless sensor network is to analyze how well the network covers the sensor field in terms of paths. Known results prior to this research, however, considered only a single source–destination pair and thus do not provide a global outlook at the given network but a local feature for the given source–destination pair. In this paper, we propose a new coverage measure of sensor networks that considers arbitrary source–destination pairs. Our novel measure naturally extends the previous concept of the best and the worst-case path-based coverage to evaluate the coverage of a given network from a global point of view, taking arbitrary paths into account.In terms of the present coverage measure, we pose the evaluation and the deployment problems for give a network; the former is to evaluate the new coverage measure of a given sensor network, and the latter is to find an optimal placement of k additional sensor nodes to improve the coverage for a given positive integer k. We present several algorithms that are either centralized or localized that solve the problems with theoretical proofs and simulation results, thus showing that our algorithms are efficient and easy to implement in practice while the quality of their outputs is guaranteed by formal proofs. For the purpose, we show an interesting relation between the present coverage measure and a certain quantity of a point set, called the bottleneck, which has been relatively well studied in other disciplines such as computational geometry and operations research.

Achieving high diversity and multiplexing gains in the asynchronous parallel relay network

A single source-destination pair communicating via a layer of parallel relay nodes under quasi-static slow fading environment is investigated. The time delays from the source to the destination via different relays are assumed to be different. For such an asynchronous environment, a new transmission scheme is constructed so as to achieve better diversity-multiplexing tradeoff (DMT). More specifically, both the source and the destination adopts orthogonal frequency division multiplexing technique to solve the asynchronous problem; the relays cooperatively apply the distributed generalised complex orthogonal design, a form of orthogonal space–time coding, for high-rate transmission. Each relay is assumed to use the adaptive amplify-and-forward relaying strategy. To optimise its outage performance, a distributed on-off power control rule applied to the relays is analytically derived and is proved to yield full spatial diversity order. Compared with an existing protocol, our proposed scheme is shown to achieve the same DMT when there are four relay nodes and better DMT when there are more. Besides, the DMT gap between our scheme and the existing one increases with the number of relay nodes. Copyright © 2013 John Wiley & Sons, Ltd.

Dynamic Congestion Games: The Price of Seasonality

We propose a model of discrete time dynamic congestion games with atomic players and a single source-destination pair. The latencies of edges are composed by free-flow transit times and possible queuing time due to capacity constraints. We give a precise description of the dynamics induced by the individual strategies of players and of the corresponding costs, either when the traffic is controlled by a planner, or when players act selfishly. In parallel networks, optimal and equilibrium behavior eventually coincides, but the selfish behavior of the first players has consequences that cannot be undone and are paid by all future generations. In more general topologies, our main contributions are three-fold. First, we show that equilibria are usually not unique. In particular, we prove that there exists a sequence of networks such that the price of anarchy is equal to n-1, where n is the number of vertices, and the price of stability is equal to 1.Second, we illustrate a new dynamic version of Braess's paradox: the presence of initial queues in a network may decrease the long-run costs in equilibrium. This paradox may arise even in networks for which no Braess's paradox was previously known.Third, we propose an extension to model seasonalities by assuming that departure flows fluctuate periodically over time. We introduce a measure that captures the queues induced by periodicity of inflows. This measure is the increase in costs compared to uniform departures for optimal and equilibrium flows in parallel networks.

Energy-efficient hybrid opportunistic cooperative protocol for single-carrier frequency division multiple access-based networks

In this study, a new energy-efficient hybrid opportunistic cooperative (HOC) transmission protocol is proposed for single-carrier frequency division multiple access (SC-FDMA)-based cooperative networks. The author considers a single source–destination pair and multiple relays network. The proposed protocol improves the energy efficiency of SC-FDMA-based networks by selecting the most energy-efficient cooperative transmission protocol from a set of available protocols according to the current channel state information. The protocols considered in the development of the HOC protocol are amplify-and-forward, decode-and-forward, compress-and-forward and estimate-and-forward. Computer simulation is done over four different scenarios of channel conditions. The obtained results show that the proposed HOC protocol significantly improves the delay-limited capacity and minimises the outage probability of SC-FDMA-based cooperative networks. The results also show that the minimum required average total power in the proposed HOC protocol is less than that of opportunistic decode-and-forward by 0.55 dB.

Power allocation in wireless multiuser multi-relay networks with distributed beamforming

This article studies optimal power allocation schemes in a multi-relay cooperating network employing amplify-and-forward (AF) protocol with multiple source–destination pairs. It is assumed that full channel state information is available at the relays. As such, distributed beamforming is employed in forwarding signals to the destinations. In this context, the authors extend recent works on distributed beamforming for a single source–destination pair to the scenario where multiple source–destination pairs are competing for the power resource at the relays. Under orthogonal transmissions of each source–destination pair, considered are the two following power allocation problems: (i) minimise the sum relay power with guaranteed quality of service (QoS) in terms of signal-to-noise ratio (SNR) at the destinations, and (ii) jointly maximise the SNR margin at the destinations subject to individual power constraints at the relays. Although these optimisation problems can be formulated as second-order conic programs (SOCP), the main contribution of this work are proposals of simple and fast converging numerical algorithms, based on the fixed point iteration framework, to efficiently solve these two problems.