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

Oikonomou, George; Phillips, Iain

doi:10.1109/dcoss.2011.5982222

Cited by 26 publications

(19 citation statements)

References 8 publications

(6 reference statements)

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“…Furthermore, Contiki and other state-of-art IoT OS do not have software support for this feature. CC2650 has 20 kB RAM, which is not a large amount for a 32-bit system, taking into account the Contiki OS footprint and the large RAM requirements for network neighbor and routing tables [12]. Not having a neighbor or a routing table entry for an active neighbor can severely reduce the performance and stability of the network [13]; consequently, it is optimal to reserve as many entries as possible, aiming for an entry for each device in the network.…”

Section: B Memory Managementmentioning

confidence: 99%

Internet of Things for smart homes: Lessons learned from the SPHERE case study

Elsts

Oikonomou

Fafoutis

et al. 2017

2017 Global Internet of Things Summit (GIoTS)

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Section: B Memory Managementmentioning

confidence: 99%

Internet of Things for smart homes: Lessons learned from the SPHERE case study

Elsts

Oikonomou

Fafoutis

et al. 2017

2017 Global Internet of Things Summit (GIoTS)

Self Cite

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“…The authors make the assumption that the routing table contains multiple candidate next hops for the same destination and they propose an algorithm for path aggregation. However, routing table size has an impact on scalability with increasing network size [32] even when the table only lists a single next hop per destination. Storing multiple candidate next hops per destination would impose further memory overheads 4 and should not be considered common practise.…”

Section: Multicast In Traditional Wsnsmentioning

confidence: 99%

“…The port of the Contiki OS for our hardware platform [32] does not support ContikiMAC yet. As a result all experiments were conducted over NullRDC.…”

Section: Hardware Experimentsmentioning

confidence: 99%

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IPv6 Multicast Forwarding in RPL-Based Wireless Sensor Networks

Oikonomou

Phillips

Tryfonas

2013

Wireless Pers Commun

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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.

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“…Gathering these functions in a single device simplifies modules programming and enables and makes it easier and more efficient their implementation, due to the modular architecture of devices. First, the use of available commercial boards such as Zigduino [6] or Zolertia Zl [7] was considered, but BatNet devices have two requirements that are a must: reduced size and the possibility of integrating a wide variety of sensors. To fulfill these requirements a low-cost and low-power processing and communication module has been designed and implemented: the BatMote (see Fig.…”

Section: Batmote: Processing and Communications Modulementioning

confidence: 99%

BatNet: A 6LoWPAN-Based Sensors and Actuators Network

Campo

Montoya

Martín

et al. 2012

Ubiquitous Computing and Ambient Intelligence

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Abstract. Improving energy efficiency in buildings is one of the goals of the Smart City initiatives and a challenge for the European Union. This paper presents a 6L0WPAN wireless transducer network (BatNet) as part of an open energy management system. This network has been designed to operate in buildings, to collect environmental information (temperature, humidity, illumination and presence) and electrical consumption in real time (voltage, current and power factor). The system has been implemented and tested in the Energy Efficiency Research Facility at CeDInt-UPM. Energy consumption in buildings, which is one of the cornerstones of the Smart Cities, accounts for between 20% and 40% of the total energy used in developed countries [1]. Gathering information related to the use of energy made by devices, users and systems within a building is useful to improve the efficiency of electricity distribution systems, since it provides accurate information to avoid peaks and dips in energy demand.Real time metering systems of electric line parameters (such as current, voltage or real power) provide accurate information related to the building electrical consumption. This information is essential to improve electricity generation and distribution in a smart grid. Most of the distribution board metering devices proposed so far only measure electric current and consequently the power consumption is calculated assuming a constant voltage from the electric line [2]. Other devices measure the line voltage as well but just on one electric line.In order to solve these problems and serve as a basis for smart cities we propose an energy management system for buildings. The system comprises a management

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

Cited by 26 publications

References 8 publications

Internet of Things for smart homes: Lessons learned from the SPHERE case study

Internet of Things for smart homes: Lessons learned from the SPHERE case study

IPv6 Multicast Forwarding in RPL-Based Wireless Sensor Networks

BatNet: A 6LoWPAN-Based Sensors and Actuators Network

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