A cross-layer architecture for service differentiation in Wireless Sensor Networks with multiple sinks

Abstract

In this paper, we are interested in the description of a cross-layer architecture that supports service differentiation for real-time and best-effort traffics in Wireless Sensor Networks (WSN). We present our mathematical model that combines parameters from network and MAC layers. We aim to estimate and to enhance the throughput of multi-hop WSNs and the stability of the forwarding queues used for real-time and besteffort traffics. We suppose at the first step that we have a wireless sensor network with a single sink then we suppose that we have the same wireless sensor network with two sinks. We study the impact of transmitting real-time and best-effort traffics on the system throughput; and we also study the impact of adding a second sink on the throughput.

CL-mWSNs: Cross Layer Model-Based QoS Centric Routing Protocol for Mission-Critical Cooperative Communication in Mobile WSNs

“…The majority of the existing approaches rely on single parameter-based routing decision-making schemes, where the emphasis is placed on augmenting PHY and MAC [3], [4], [9], [12], SD functions [9], congestion avoidance at MAC [19] etc. However, very few efforts have been made to make the routing decision while considering the type of data and its priority, to ensure deadline sensitive communication [12]. On the contrary, it is a fact that inclusion of these all factors, network condition-aware routing with synchronized cross-layer information may improve BFN selection and routing decisions.…”

“…On the contrary, it is a fact that inclusion of these all factors, network condition-aware routing with synchronized cross-layer information may improve BFN selection and routing decisions. With this motivation, in this research a reference model has been developed that combines the major efficacies of multiple contributions made, such as in [3], [4], [9], [12], [19], [22]. Although in [3], the authors considered only the MAC and PHY layers where throughput and link-outage probability (at MAC) were used to perform PHY switching control, they could not address other aspects, such as packet transmission rate or packet velocity of a node, which is a must for deadline-sensitive, mission-critical communication.…”

“…This model could not offer the provision of better SD. Noticeably, the aforementioned routing cross-layer models [3], [4], [9], [12], [19] have implemented a cross-layer model, but for static WSNs only. They have not addressed the exceedingly dynamic topology of a mobile WSN.…”

“…Their proposed cross-layer model adaptively adjusted the control period to achieve improved resource utilization while maintaining timely data delivery. Mezouary et al [12] developed a cross-layer model-based SD scheme to classify data as RTD and NRT traffic in WSNs. They combined the parameters from the MAC layer and the network layer to augment throughput.…”

A Cross-Layer Optimization QoS Scheme in Wireless Multimedia Sensor Networks

“…Queues are assigned different transmission priorities according to the types of applications that the queues support. The existing QoS schemes providing DiffServ can be divided into four categories of algorithms: media access control schemes [3,4], scheduling schemes [5][6][7][8][9][10][11], routing schemes [12][13][14], and cross-layer control schemes [15][16][17]. However, in these works, after initial allocation, the priorities of the queues cannot be re-adjusted according to the real-time end-to-end situation.…”