Experiences from porting the Contiki operating system to a popular hardware platform

In contrast to original belief, recent work has demonstrated the viability of IPv6-based Wireless Sensor Networks (WSNs). This has led to significant research and standardization efforts with outcomes such as the "IPv6 over Low-Power Wireless Personal Area Networks " (6LoWPAN) specification. The Contiki embedded operating system is an important open source, multi-platform effort to implement 6LoWPAN functionality for constrained devices. Alongside its RFC-compliant TCP/IP stack (uIP), it provides support for 6LoWPAN and many related standards. As part of our work, we have made considerable fixes and enhancements to one of Contiki's ports. In the process, we made significant optimizations and a thorough evaluation of Contiki's memory and code footprint characteristics, focusing on network-related functionality. In this paper we present our experiences from the porting process, we disclose our optimizations and demonstrate their significance. Lastly, we discuss a method of using Contiki to deploy an embedded Internet-to-6LoWPAN router. Our porting work has been made available to the community under the terms of the Contiki license

Stateless multicast forwarding with RPL in 6LowPAN sensor networks

Recent research efforts have resulted in efficient support for IPv6 in Low power Wireless Personal Area Networks (6LoWPAN), with the "IPv6 Routing Protocol for Low power and Lossy Networks" (RPL) being on the forefront as the state of the art routing approach. However, little attention has been paid to IPv6 multicast for networks of constrained devices. The "Multicast Forwarding Using Trickle" (Trickle Multicast) internet draft is one of the most noteworthy efforts, while RPL's specification also attempts to address the area but leaves many questions unanswered. In this paper we expose our concerns about the Trickle Multicast (TM) algorithm, backed up by thorough performance evaluation. We also introduce SMRF, an alternative multicast forwarding mechanism for RPL networks, which addresses TM's drawbacks. Simulation results demonstrate that SMRF achieves significant delay and energy efficiency improvements at the cost of a small increase in packet loss. We have extended the TCP/IP engine of the Contiki embedded Operating System to support both algorithms. Both implementations have been made available to the community. © 2012 IEEE

IPv6 multicast forwarding in RPL-based wireless sensor networks

In wireless sensor deployments, network layer multicast can be used to improve the bandwidth and energy efficiency for a variety of applications, such as service discovery or network management. However, despite efforts to adopt IPv6 in networks of constrained devices, multicast has been somewhat overlooked. The Multicast Forwarding Using Trickle (Trickle Multicast) internet draft is one of the most noteworthy efforts. The specification of the IPv6 routing protocol for low power and lossy networks (RPL) also attempts to address the area but leaves many questions unanswered. In this paper we highlight our concerns about both these approaches. Subsequently, we present our alternative mechanism, called stateless multicast RPL forwarding algorithm (SMRF), which addresses the aforementioned drawbacks. Having extended the TCP/IP engine of the Contiki embedded operating system to support both trickle multicast (TM) and SMRF, we present an in-depth comparison, backed by simulated evaluation as well as by experiments conducted on a multi-hop hardware testbed. Results demonstrate that SMRF achieves significant delay and energy efficiency improvements at the cost of a small increase in packet loss. The outcome of our hardware experiments show that simulation results were realistic. Lastly, we evaluate both algorithms in terms of code size and memory requirements, highlighting SMRF's low implementation complexity. Both implementations have been made available to the community for adoption

Adaptive and context-aware service discovery for the Internet of Things

The Internet of Things (IoT) vision foresees a future Internet encompassing the realm of smart physical objects, which offer hosted functionality as services. The role of service discovery is crucial when providing application-level, end-to-end integration. In this paper, we propose trendy: a RESTful web services based Service Discovery protocol to tackle the challenges posed by constrained domains while offering the required interoperability. It provides a service selection technique to offer the appropriate service to the user application depending on the available context information of user and services. Furthermore, it employs a demand-based adaptive timer and caching mechanism to reduce the communication overhead and to decrease the service invocation delay. trendy’s grouping technique creates location-based teams of nodes to offer service composition. Our simulation results show that the employed techniques reduce the control packet overhead, service invocation delay and energy consumption. In addition, the grouping technique provides the foundation for group-based service mash-ups and localises control traffic to improve scalability

TRENDY: an adaptive and context-aware service discovery protocol for 6LoWPANs

We propose, TRENDY, a new registry-based Service Discovery protocol with context awareness. It uses CoAP-based RESTful web services to provide a standard interoperable interface which can be easily translated from HTTP. In addition, TRENDY introduces an adaptive timer and grouping mechanism to minimise control overhead and energy consumption. TRENDY's grouping is based on location tags to localise status maintenance traffic and to compose and offer new group based services. Our simulation results show that TRENDY techniques reduce the control traffic considerably and also reduce the energy consumption, while offering the optimal service selection