A Combinational Perspective in Stimulating Cooperation in Mobile Ad Hoc Networks

In wireless ad hoc networks cooperation among nodes cannot always be assumed since nodes with limited resources and different owners are capable of making independent decisions. Cooperation problems in topology control and packet forwarding tasks have been mostly studied separately but these two tasks are not independent. Considering a joint cooperation problem by taking into account dependencies between tasks will result in more reliable and efficient networks. In this paper topology control definition is extended to cover cooperation problem in both packet forwarding and topology control in a single problem. In this definition nodes have to adjust their transmission power and decide on their relay role. This paper models the interactions of nodes as a potential game with two-dimensional utility function. The presented model, named TCFORCE (Topology Control packet FORwarding Cooperation Enforcement), preserves the network connectivity and reduces the energy consumption by providing cooperative paths between all pairs of nodes in the network.     

CPTR: conditional probability tree based routing in opportunistic networks

In opportunistic networks due to the inconsistency of the nodes link, routing is carried out dynamically and we cannot use proactive routes. In these networks, nodes use opportunities gained based on store-carry-forward patterns to forward messages. Every node that receives a message when it encounters another node makes decision regarding the forwarding or not forwarding the node encountered. In some previous methods, the recognition of whether encounter with current node is considered as an appropriate opportunity or not has been carried out based on the comparison of the probability of carrier node and the node encountered. In these methods, if the message is delivered to the encountered node, a better opportunity would be lost. To fight with this challenge we have posed CPTR method by using conditional probability tree method through which in addition to the probability of the delivery of carrier and encountered nodes’ message delivery, the opportunities for after encounter will be involved in messages’ forwarding. Results of simulation showed that the proposed method can improve the ratio of delivery and delay of message delivery compared to other similar methods in networks with limited buffer.     

Design a novel routing criterion based on channel features and internal backup routes for cognitive radio network

Telecommunication Systems - In the routing process, the cost (or weight) of routes determine via a function named routing criterion. Therefore, the design of Optimal Routing Criterion (ORC) is one...     

Joint routing and channel assignment using online learning in cognitive radio networks

Cognitive radio networks (CRNs) are the solution for the problem of underutilizing the licensed spectrum for which there are more requests in the last couple of decades. In CRNs, Secondary users (SUs) are permitted to access opportunistically the licensed spectrum owned by primary users (PUs). In this paper, we address the problem of joint routing and channel assignment for several flows generated by source SUs to a given destination. We consider a more realistic model based on Markov modulated Poisson process for modeling the PUs traffic at each channel and the SUs try to exploit short lived spectrum holes between the PUs packets at the selected channel. The SUs want to cooperatively minimize the end-to-end delay of source SUs flows meanwhile the quality of service requirements of the PUs would be met. To consider partial observation of SUs about PUs activity at all channels and quick adaptation of SUs decisions to environment changes and cooperative interaction of SUs, we use decentralized partially observable markov decision process for modeling the problem. Then, an online learning based scheme is proposed for solving the problem. Simulation results show that the performance of the proposed method and the optimal method is close to each other. Also, simulation results show that the proposed method greatly outperforms related works at control of interference to the PUs while maintains the end-to-end delay of SU flows in a low level.

     

Sharing spray and wait routing algorithm in opportunistic networks

Due to the instability and intermittent connectivity of links among the nodes and the lack of connectivity in opportunistic network, it is not feasible to use common routing for delivering messages. The only practical method for routing and delivering messages is to use the store-carry-forward routing method. As a case in point, spray and wait is considered to be one of the most appropriate routing methods. The efficiency of this method depends directly on the proper selection of the next hop and the number of copies when it encounters a node. In this paper, a method was proposed that constantly selects the next node and considers the number of copies a node can deliver. In the proposed method, the selection of the next node and the number of message copies to be transmitted by the next hop are based on message carrying time and the probability of message delivery. The network model, based on Markov chain, is extended for analysis. Simulation and analysis results showed that significant enhancement is obtained with the proposed method when measuring metrics such as delay, delivery ratio and copy do comparisons with similar methods.     

A novel model for implicit cooperation between primary users and secondary users in cognitive radio‐cooperative communication systems

Recently, cooperative communications are used to improve the communications performance in cognitive radio networks. In this paper, we present a new model for implicit cooperation between primary users and secondary users (SUs), where SUs transparently relay packets of primary transmitters (PTs) towards their primary receivers encouraging PTs to reduce their transmit power, which in turn will reduce the total interference at some intended secondary receivers (SRs). Secondary relays work as full‐duplex amplify‐and‐forward (AF) cooperative nodes. The system is modeled as a multi‐armed restless bandit problem where the optimal policy for joint relay selection and transmit power allocation is obtained in a distributed way taking both instantaneous channel states and residual energy into consideration. We solve the problem using primal‐dual priority‐index heuristic, which can reduce the online computations and implementation complexity. Simulation results show that this model can benefit both sides where the energy consumption at PTs is reduced significantly and signal to interference plus noise ratio (SINR) at the intended SUs is increased about 50% in average.     

Near‐optimal online routing in opportunistic networks

In opportunistic networks, nodes communicate intermittently based on store‐carry‐forward paradigm while exploiting node mobility. The challenge is to determine the ideal nodes to deliver the messages since there is no end‐to‐end connectivity. The nodes might make this decision based on the data sensed from the network. This technique is not ideal in scenarios where the speed of changes in the network topology is greater than the speed at which the nodes can collect info on the network, which might, in turn, be restricted due to usage constraints and uncertainty of knowledge about future contacts. To tackle the problems raised by the non‐deterministic environments, in this paper, a stochastic optimization model and corresponding algorithm are developed to find the optimal routes by considering the short and long‐term impact of choices, ie, the next hop. Herein, we first propose a stochastic model to resolve the routing problem by identifying the shortest path. In the second step, we show that the optimal solution of the proposed model can be determined in polynomial time. An online algorithm is then proposed and analyzed. The algorithm is O( lognρ ) competitive considering the number of nodes and their associated energy. This model can take advantage of the unexpected meets to make the routing more elastic in a short time of contact and with less of a burden on the buffer. The simulation results, against the prominent algorithms, demonstrate significant improvement of the proposed approach in delivery and average delay ratio.     

Design of optimum criterion for opportunistic multi-hop routing in cognitive radio networks

The instability of operational channels on cognitive radio networks (CRNs), which is due to the stochastic behavior of primary users (PUs), has increased the complexity of the design of the optimal routing criterion (ORC) in CRNs. The exploitation of available opportunities in CRNs, such as the channel diversity, as well as alternative routes provided by the intermediate nodes belonging to routes (internal backup routes) in the route-cost (or weight) determination, complicate the ORC design. In this paper, to cover the channel diversity, the CRN is modeled as a multigraph in which the weight of each edge is determined according to the behavior of PU senders and the protection of PU receivers. Then, an ORC for CRNs, which is referred to as the stability probability of communication between the source node and the destination node (SPC_SD), is proposed. SPC_SD, which is based on the obtained model, internal backup routes, and probability theory, calculates the precise probability of communication stability between the source and destination. The performance evaluation is conducted using simulations, and the results show that the end-to-end performance improved significantly.     

A Rate-Distortion Based Aggregation Method Using Spatial Correlation for Wireless Sensor Networks

Today we are witnessing an amazing growth of wireless sensor networks due to many factors including but limited to reducing cost of semiconductor components, rapid deployment of wireless networks, and attention to low-power aspect that makes these networks suitable for energy sensitive applications to a large extent. The power consumption requirement has raised the demand for the new concepts such as data aggregation. Data correlation plays an important role in an efficient aggregation process. This paper introduces a new correlation-based aggregation algorithm called RDAC (Rate Distortion in Aggregation considering Correlation) that works based on centralized source coding. In our method, by collecting correlated data at an aggregation point while using the Rate-Distortion (RD) theory, we can reduce the load of data transmitted to the base station by considering the maximum tolerable distortion by the user. To the best of our knowledge, nobody has yet used the RD theory for the data aggregation in wireless sensor networks. In this paper, a mathematical model followed by implementations demonstrates the efficiency of the proposed method under different conditions. By using the unique features of the RD theory, the correlation matrix and observing the behavior of the proposed method in different network topologies, we can find the mathematical upper and lower bounds for the amount of aggregated data in a randomly distributed sensor network. The bounds not only determine the upper and lower limits of the data compressibility, it also makes possible the estimation of the required bit count of the network without having to invoke the aggregation algorithm. This method therefore, allows us to have a good estimation of the amount of energy consumed by the network.     

A Reinforcement Learning Based Routing in Cognitive Radio Networks for Primary Users with Multi-stage Periodicity

Wireless Personal Communications - Designing an efficient routing protocol for cognitive radio networks is critical due to the dynamic behavior of the primary users. Based on empirical studies, the...