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This work is devoted to solving the problem of multicriteria multihop routing in vehicular ad hoc networks (VANETs), aiming at three goals: 1) increasing the end-to-end delivery ratio; 2) reducing the end-to-end latency; and 3) minimizing the network overhead. To this end and beyond the state of the art, heuristic routing for vehicular networks (HERO), which is a distributed routing protocol for urban environments, encapsulating two main components, is proposed. The first component, road-segment selection, aims to prioritize the road segments based on a heuristic function that contains two probability distributions, namely, shortest distance distribution (SDD) and connectivity distribution (CD). The mass function of SDD is the product of three quantities: 1) the perpendicular distance; 2) the dot-production angle; and 3) the segment length. On the other hand, the mass function of CD considers two quantities: 1) the density of vehicles and 2) the interdistance of vehicles on the road segment. The second component, vehicle selection, aims to prioritize the vehicles on the road segment based on four quantities: 1) the relative speed; 2) the movement direction; 3) the available buffer size; and 4) signal fading. The simulation results showed that HERO achieved a promising performance in terms of delivery success ratio, delivery delay, and communication overhead.

Wireless sensor networks (WSNs) with a static sink suffer from concentrated data traffic in the vicinity of the sink, which increases the burden on the nodes surrounding the sink, and impels them to deplete their batteries faster than other nodes in the network. Mobile sinks solve this corollary by providing a more balanced traffic dispersion, by shifting the traffic concentration with the mobility of the sink. However, it brings about a new expenditure to the network, where prior to delivering data, nodes are obligated to procure the sink’s current position. This paper proposes Tuft, a novel hierarchical tree structure that is able to avert the overhead cost from delivering the fresh sink’s position while maintaining a uniform dispersion of data traffic concentration. Tuft appropriates the mobility of the sink to its advantage, to increase the uniformity of energy consumption throughout the network. Moreover, we propose Tuft-Cells, a distributed dissemination protocol that models data routing as a Multi-Criteria Decision Making (MCDM) in three steps. To begin with, each criterion constitutes a random variable defined by a mass function. Each of these cirterion serves a proportionately distinguishable alternative, and hence, may conflict. Therefore, the Analytic Hierarchy Process (AHP) quantifies the relationship between criteria. Finally, the final forwarding decision is derived by a weighted aggregation. Tuft is compared with state-of-the-art protocols, and the performance evaluation illustrates that our protocol adheres to the requirements of WSNs, in terms of energy consumption, and success ratio, considering the additional overhead cost brought by the mobility of the sink.

Mobile sinks have advantages such as solving the hotspot problem which occurs because some sensor nodes deplete energy faster than others and enhancing energy balance among the sensor nodes. However, sink mobility raises two challenges, frequent location updates and packets delivery delay. To tackle these two problems, this work proposes a protocol that involves two mechanisms. First, to reduce the frequent location updates of the mobile sink to all sensor nodes, we proposed an accessible virtual structure (Double Ring) that acts as an intermediate structure between the sink and the sensor nodes when exchanging metadata and query packets. Second, to accelerate packets delivery, we proposed a heuristic data dissemination protocol, called HDD, in which the heuristic function is based on four values, direction, transmission distance, perpendicular distance, and residual energy. The experimental results showed that our proposed protocol outperforms the state of art protocols in terms of energy consumption, delivery rate, latency, and network lifetime.

This article extends the promising software-defined networking technology to wireless sensor networks to achieve two goals: 1) reducing the information exchange between the control and data planes, and 2) counterbalancing between the sender’s waiting-time and the duplicate packets. To this end and beyond the state-of-the-art, this work proposes an SDN-based architecture, namely MINI-SDN, that separates the control and data planes. Moreover, based on MINI-SDN, we propose MINI-FLOW, a communication protocol that orchestrates the computation of flows and data routing between the two planes. MINI-FLOW supports uplink, downlink and intra-link flows. Uplink flows are computed based on a heuristic function that combines four values, the hops to the sink, the Received Signal Strength (RSS), the direction towards the sink, and the remaining energy. As for the downlink flows, two heuristic algorithms are proposed, Optimized Reverse Downlink (ORD) and Location-based Downlink(LD). ORD employs the reverse direction of the uplink while LD instantiates the flows based on a heuristic function that combines three values, the distance to the end node, the remaining energy and RSS value. Intra-link flows employ a combination of uplink/downlink flows. The experimental results show that the proposed architectureand communication protocol perform and scale well with both network size and density, considering the joint problem of routing and load balancing.

In wireless sensor networks, routing protocols with immutable network policies lacking the flexibility are generally incapable of maintaining desired performance due to the complicated and changeable environment situations and application requirements. The proposed “Flexible Routing Computing Approach (FRCA)” is a novel distributed and probabilistic computing approach capable of modifying or upgrading routing policies on the fly with low cost, which effectively enhances the flexibility of routing protocols. FRCA models the routing metric as a forwarding probability distribution for routing decisions. This model depends on three elements, the physical quantities collected at sensor nodes, the built-in base math functions, and the routing parameters. These elements are all user-oriented and can be specified to implement multifarious complicated network policies meeting different performance requirements. More significantly, through distributing routing parameters from the sink to end nodes, operators are allowed to adjust network policies on the fly without the interruption of network services. Through extensive performance evaluation studies and simulations, the results demonstrated that routing protocols designed based on FRCA could achieve better performance compared to its state-of-the-art counterparts regarding network lifetime, energy consumption, and duplicate packets as well as ensure high flexibility during network policies modification or upgrade.

In wireless sensor networks (WSNs), it is inappropriate to use conventional unicast routing due to the broadcast storm problem and spatial diversity of communication links. Opportunistic Routing (OR) benefits the low duty-cycled WSNs by prioritizing the multiple candidates for each node instead of selecting one node as in conventional unicast routing. OR reduces the sender waiting time, but it also suffers from the duplicate packets problem due to multiple candidates waking up simultaneously. The number of candidates should be restricted to counterbalance between the sender waiting time and duplicate packets. In this paper, software-defined networking (SDN) is adapted for the flexible management of WSNs by allowing the decoupling of the control plane from the sensor nodes. This study presents an SDN based load balanced opportunistic routing for duty-cycled WSNs that addresses two parts. First, the candidates are computed and controlled in the control plane. Second, the metric used to prioritize the candidates considers the average of three probability distributions, namely transmission distance distribution, expected number of hops distribution and residual energy distribution so that more traffic is guided through the nodes with higher priority. Simulation results show that our proposed protocol can significantly improve the network lifetime, routing efficiency, energy consumption, sender waiting time and duplicate packets as compared with the benchmarks.

This paper presents a protocol called Heuristic Routing with Infrastructure Nodes (HRIN) for data dissemination in vehicular networks. The main goals of this work aims to increase the packet delivery ratio and reduce the end-to-end delay. To achieve these goals, we propose two heuristic functions for Road Segments Selection (RSS) and Intermediate Nodes Selection (INS). Further, we propose the deployment of the Road-side Unit (RSU) on each road junction. RSUs can further assist the vehicles in data dissemination. The RSS is the combination of two probability functions, shortest distance, and higher connectivity. On the other hand, the INS is based on four quantities, vehicle's speed difference, vehicle's moving direction, number of packets on the vehicle, and signal fading. The simulation results of our proposed protocol achieved reasonable results for packet delivery ratio and end-to-end delay compared to the existing protocols.

this paper addresses the uplink and downlink routing mechanisms in software defined wireless sensor network (SDN-WSN). We proposed an integrated communication protocol, called MINI-FLOW, that surrounds three data routing mechanism, the uplink routing (from the end nodes to the controller), the downlink routing (from the controller to the end nodes) and the information reporting in the network initialization level (i.e., when the controller knows nothing about the end nodes). The routing mechanism is designed based on a heuristic function that captures three values, the number of hops to the sink, the Received Signal Strength (RSS) and the remaining energy. The experimental results show that MINI-FLOW scales well with both network size and density, considering the combined problem of routing and load balancing.