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 (SPCSD), is proposed. SPCSD, 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. © 2018 ETR

Efficient application deployment in fog-enabled infrastructures

Fog computing is a paradigm that extends cloud computing services to the edge of the network in order to support delay-sensitive Internet of Things (IoT) services. One of the most promising use-cases of fog computing is Smart City scenarios. Fog computing can substantially improve the quality of citywide services by reducing response delays. Owing to geographically distributed and resource-constrained fog nodes and a multitude of IoT devices in Smart Cities, efficient service deployment and end device traffic routing are quite challenging. Therefore, in this paper, we present an Integer Linear Programming (ILP) formulation for the Joint Application Component Placement and Traffic Routing (JAcPTR) problem in which users' delay requirements and the limited traffic processing capacity of application instances are considered. Besides, the JAcPTR enables users and infrastructure managers to easily enforce their locality and management requirements in the deployment of application instances. To cope with the considerably high execution time in large instances of the JAcPTR problem, we propose a fast polynomial-time heuristic to efficiently solve the problem. The performance of the proposed heuristic has been evaluated through extensive simulation. Results show that in large instances of the problem, while the state-of-the-art Mixed Integer Linear Programming (MILP) solver fails to obtain a solution in 50% of the simulation runs in 300 seconds, our proposed heuristic can obtain a near-optimal solution in less than one second

Spatial correlation aware protocols for efficient data aggregation of moving object in wireless sensor networks

In Wireless Sensor Networks (WSNs), power consumption of sensor nodes is the main constraint. Emerging in-network aggregation techniques are increasingly being sought after to address this key challenge and to save precious energy. One application of WSNs is in data gathering of moving objects. In order to achieve complete coverage, this type of application requires spatially dense sensor deployment, which, under close observation, exhibits important spatial correlation characteristics. The Rate Distortion (RD) theory is a data aggregation technique that can take advantage of this type of correlation with the help of a cluster based communication model. Due to object movement, the Rate-Distortion based aggregation incurs high computation overhead. This paper first introduces an introduction for the rate-distortion based moving object data aggregation model. Then, to overcome the high computation overhead, several low overhead protocols are proposed based on this model, namely, a static cluster-based protocol that uses static clustering, a dynamic cluster-based protocol that uses dynamic clustering, and a hybrid protocol which takes advantage of the other two protocols. Simulation results show that with the hybrid method, it is possible to save more than 36% of the nodes’ energy when compared to the other approaches

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

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 of the most crucial issues in routing. The existence of unstable channels in Cognitive Radio Network (CRN) has caused the design of ORC in CRN converts to a challenging topic. In this paper, at first, the CRN is modeled as a multigraph where each vertex shows one secondary user (SU) and each edge a channel between two neighboring SUs. In this multigraph, each edge has two weights; the first weight is determined based on the behavior of PU senders and protection of PU receivers, and second weight based on the channel bandwidth. At the next step, an ORC for CRN, referred to as ETEDBEST, is proposed. ETEDBEST is designed based on the obtained model, routes provided by the intermediate nodes belonging to the route and probability theory that calculates the delay between two SUs in CRN precisely. Performance evaluation is conducted through simulations, the results show that end-to-end performance improved significantly. © 2018, Springer Science+Business Media, LLC, part of Springer Nature

LDAOR - Location and Direction Aware Opportunistic Routing in Vehicular Ad hoc Networks

Routing in Vehicular Ad hoc Networks (VANETs) has found significant attention because of its unique features such as lack of energy constraints and high-speed vehicles applications. Besides, since these networks are highly dynamic, design process of routing algorithms suitable for an urban environment is extremely challenging. Appropriate algorithms could be opportunistic routing (OR) where traffic transmission is performed using the store-carry-forward mechanism. An efficient OR mechanism, called Location and Direction Aware Opportunistic Routing (LDAOR), is proposed in this paper. It is based on the best neighbor node selection by using vehicles positions, vehicles directions, and prioritization of messages from buffers, based on contact histories and positions of neighbor nodes to destination. In LDAOR, when multiple nodes make contact with a carrier node, the closest neighbor node to destination is selected as the best forwarder. However, when only one node makes contact with the carrier node, the message is delivered to it if it moves toward the destination. Using the ONE simulator, the obtained performance evaluation results show that the LDAOR operates better than conventional OR algorithms. The LDAOR not only increases delivery rate, but also reduces network overhead, traffic loss, and number of aborted messages