Wireless Sensor Networks (WSNs) are attracting more and more interest since they offer a low-cost solution to the problem of providing a means to deploy large sensor networks in a number of application domains. We believe that a crucial aspect to facilitate WSN diffusion is to make them interoperable with external IP networks. This can be achieved by using the 6LoWPAN protocol stack. 6LoWPAN enables the transmission of IPv6 packets over WSNs based on the IEEE 802.15.4 standard. IPv6 packet size is considerably larger than that of IEEE 802.15.4 data frame. To overcome this problem, 6LoWPAN introduces an adaptation layer between the network and data link layers, allowing IPv6 packets to be adapted to the lower layer constraints. This adaptation layer provides fragmentation and header compression of IP packets. Furthermore, it also can be involved in routing decisions. Depending on which layer is responsible for routing decisions, 6LoWPAN divides routing in two categories: mesh under if the layer concerned is the adaptation layer and route over if it is the network layer. In this paper we analyze different routing solutions (route over, mesh under and enhanced route over) focusing on how they forward fragments. We evaluate their performance in terms of latency and energy consumption when transmitting IP fragmented packets. All the tests have been performed in a real 6LoWPAN implementation. After consideration of the main problems in forwarding of mesh frames in WSN, we propose and analyze a new alternative scheme based on mesh under, which we call controlled mesh under.
Abstract:In this paper we present the design and implementation of the Constrained Application Protocol (CoAP) for TinyOS, which we refer to as TinyCoAP. CoAP seeks to apply the same application transfer paradigm and basic features of HTTP to constrained networks, while maintaining a simple design and low overhead. The design constraints of Wireless Sensor Networks (WSNs) require special attention in the design process of the CoAP implementation. We argue that better performance and minimal resource consumption can be achieved developing a native library for the operating system embedded in the network. TinyOS already includes in its distribution an implementation of CoAP called CoapBlip. However, this is based on a library not originally designed to meet the requirements of TinyOS. We demonstrate the effectiveness of our approach by a comprehensive performance evaluation. In particular, we test and evaluate TinyCoAP and CoapBlip in a real scenario, as well as solutions based on HTTP. The evaluation is performed in terms of latency, memory occupation, and energy consumption. Furthermore, we evaluate the reliability of each solution by measuring the goodput obtained in a channel affected by Rayleigh fading. We also include a study on the effects that high workloads have on a server.
In this paper, we present the design of a Constrained Application Protocol (CoAP) proxy able to interconnect Web applications based on Hypertext Transfer Protocol (HTTP) and WebSocket with CoAP based Wireless Sensor Networks. Sensor networks are commonly used to monitor and control physical objects or environments. Smart Cities represent applications of such a nature. Wireless Sensor Networks gather data from their surroundings and send them to a remote application. This data flow may be short or long lived. The traditional HTTP long-polling used by Web applications may not be adequate in long-term communications. To overcome this problem, we include the WebSocket protocol in the design of the CoAP proxy. We evaluate the performance of the CoAP proxy in terms of latency and memory consumption. The tests consider long and short-lived communications. In both cases, we evaluate the performance obtained by the CoAP proxy according to the use of WebSocket and HTTP long-polling.
In this paper, we propose a modification of the observe extension of CoAP to include Quality of Service (QoS) support for timeliness. The proposed QoS support is based on delivery priority. Nodes are able to express the priority order with which they wish to be notified. Furthermore, they are also able to specify which notification they want to receive. We classify the notifications in two categories: Critical and Non-Critical. The provided QoS is the result of a negotiation between the client and server. The client demands a certain degree of QoS according to its role. The server could accept or negotiate it. This choice depends on the availability of server and network resources. We evaluate our proposal in a real Wireless Sensor Network. An e-health application has been chosen as target of our tests. The performance evaluation is done in terms of average delay, energy consumption and delivery ratio.Postprint (published version
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