Improvements to end-to-end performance of low-power wireless networks

Over the last decades, wireless technologies have become an important part of our daily lives. A plentitude of new types of networks based on wireless technologies have emerged, often replacing wired solutions. In this development, not only the number and the types of devices equipped with wireless transceivers have significantly increased, also the variety of wireless technologies has grown considerably. Moreover, Internet access for wireless devices has paved the way for a large variety of new private, business, and research applications. Great efforts have been made by the research community and the industry to develop standards, specifications, and communication protocols for networks of constrained devices, we refer to as Wireless Sensor Networks (WSNs). The Institute of Electrical and Electronics Engineers (IEEE) defined the 802.15.4 standard for Personal Area Networks (PANs). With the introduction of an adaptation layer which makes IEEE 802.15.4 networks IPv6-capable, interconnecting billions of constrained devices has become possible and is expected to become a reality in the near future. The vision that embraces the idea of interweaving Internet technology with any type of smart objects, such as wearable devices or sensors of a WSN, is called the Internet of Things (IoT). The main goal of this thesis is the improvement of the performance of low-power wireless networks. Given the wide scope of application scenarios and networking solutions proposed for such networks, the development and optimization of communication protocols for wireless low-power devices is a challenging task: The hardware restrictions of constrained devices, specific application scenarios that may vary from one network to another, and the integration of WSNs into the IoT require new approaches to the design and evaluation of communication protocols. To face these challenges and to find solutions for them, research needs to be carried out. Mechanisms and parameter settings of communication protocol stacks for WSNs that are crucial to the network performance need to be identified, optimized, and complemented by adding new ones. The first contribution of this thesis is the improvement of end-to-end performance for IEEE 802.15.4-based PANs, where default parameter settings of common communication protocols are analyzed and evaluated with regard to their impact on the network performance. Physical evaluations are carried out in a large testbed, addressing the important question of whether the default and allowed range settings defined for common communication protocols are efficient or whether alternative settings may yield a better performance. The second contribution of this thesis is the improvement of end-to-end performance for ZigBee wireless HA networks. ZigBee is an important standard for low-power wireless networks and the investigations carried out address the crucial lack of investigation the ZigBee HA performance evaluations through physical experiments and potential ways to improve the network performance based on these experiments. Eventually, this thesis focuses on the improvement of the congestion control (CC) mechanism applied by the Constrained Application Protocol (CoAP) used in IoT communications. For the handling of the possible congestion in the IoT produced by the plethora of the devices and/or link errors innate to low-power radio communications, the default CC mechanism it lacks an advanced CC algorithm. Given CoAP's high relevance for IoT communications, an advanced CC algorithm should be capable of adapting to these particularities of IoT communications. This thesis contributes to this topic with the design and optimization of the CoAP Advanced Congestion Control/Simple (CoCoA) protocol, an advanced CC mechanism for CoAP.The investigations of advanced CC mechanisms for CoAP involve extensive performance evaluations in simulated networks and physical experiments in real testbeds using different communication technologies.

[1]  Lars Eggert Congestion Control for the Constrained Application Protocol (CoAP) , 2011 .

[2]  Reiner Ludwig,et al.  The peak-hopper: a new end-to-end retransmission timer for reliable unicast transport , 2004, IEEE INFOCOM 2004.

[3]  Özgür B. Akan,et al.  Event-to-sink reliable transport in wireless sensor networks , 2005, IEEE/ACM Transactions on Networking.

[4]  A. Varga,et al.  THE OMNET++ DISCRETE EVENT SIMULATION SYSTEM , 2003 .

[5]  Geng Wu,et al.  M2M: From mobile to embedded internet , 2011, IEEE Communications Magazine.

[6]  Sally Floyd,et al.  Metrics for the Evaluation of Congestion Control Mechanisms , 2008, RFC.

[7]  Jon Postel,et al.  Transmission Control Protocol , 1981, RFC.

[8]  Pascal Thubert,et al.  Objective Function Zero for the Routing Protocol for Low-Power and Lossy Networks (RPL) , 2012, RFC.

[9]  Adam Dunkels,et al.  Contiki - a lightweight and flexible operating system for tiny networked sensors , 2004, 29th Annual IEEE International Conference on Local Computer Networks.

[10]  Carsten Bormann,et al.  Observing Resources in CoAP , 2010 .

[11]  Philip Levis,et al.  The β-factor: measuring wireless link burstiness , 2008, SenSys '08.

[12]  Carsten Bormann,et al.  6LoWPAN: The Wireless Embedded Internet , 2009 .

[13]  Min Soo Kang,et al.  An efficient and reliable data transmission control method for relaxing congestion problem in ZigBee network , 2008, ICUIMC '08.

[14]  Mohamed F. Younis,et al.  A survey on routing protocols for wireless sensor networks , 2005, Ad Hoc Networks.

[15]  Stan Ratliff,et al.  Dynamic MANET On-demand (AODVv2) Routing , 2013 .

[16]  Carsten Bormann,et al.  Terminology for Constrained-Node Networks , 2014, RFC.

[17]  Robert Tappan Morris,et al.  a high-throughput path metric for multi-hop wireless routing , 2005, Wirel. Networks.

[18]  Byoungchul Ahn,et al.  A Reverse AODV Routing Protocol in Ad Hoc Mobile Networks , 2006, EUC Workshops.

[19]  Adam Dunkels,et al.  Distributed tcp caching for wireless sensor networks , 2004 .

[20]  Adam Dunkels,et al.  Increasing ZigBee network lifetime with X-MAC , 2008, REALWSN '08.

[21]  Charles E. Perkins,et al.  Ad hoc On-Demand Distance Vector (AODV) Routing , 2001, RFC.

[22]  Silvia Santini,et al.  Connecting things to the web using programmable low-power WiFi modules , 2011, WoT '11.

[23]  Qin Wang,et al.  Energy Consumption Model for Power Management in Wireless Sensor Networks , 2007, 2007 4th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks.

[24]  Lothar Thiele,et al.  pTunes: runtime parameter adaptation for low-power MAC protocols , 2012, IPSN.

[25]  Jin-Shyan Lee,et al.  Performance evaluation of ZigBee-based sensor networks using empirical measurements , 2012, 2012 IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems (CYBER).

[26]  Wendi B. Heinzelman,et al.  Negotiation-Based Protocols for Disseminating Information in Wireless Sensor Networks , 2002, Wirel. Networks.

[27]  Philip Levis,et al.  The case for a network protocol isolation layer , 2009, SenSys '09.

[28]  Carles Gomez,et al.  Impact of LQI-Based Routing Metrics on the Performance of a One-to-One Routing Protocol for IEEE 802.15.4 Multihop Networks , 2010, EURASIP J. Wirel. Commun. Netw..

[29]  Ricardo Campanha Carrano,et al.  Survey and Taxonomy of Duty Cycling Mechanisms in Wireless Sensor Networks , 2014, IEEE Communications Surveys & Tutorials.

[30]  Dominique Barthel,et al.  Routing Metrics Used for Path Calculation in Low-Power and Lossy Networks , 2012, RFC.

[31]  Yong Yao,et al.  The cougar approach to in-network query processing in sensor networks , 2002, SGMD.

[32]  Saverio Mascolo,et al.  Performance evaluation and comparison of Westwood+, New Reno, and Vegas TCP congestion control , 2004, CCRV.

[33]  H. Søgaard,et al.  ZigBee-based wireless sensor networks for monitoring animal presence and pasture time in a strip of new grass , 2008 .

[34]  Siarhei Kuryla,et al.  RPL: IPv6 Routing Protocol for Low power and Lossy Networks , 2010 .

[35]  Adam Dunkels,et al.  The ContikiMAC Radio Duty Cycling Protocol , 2011 .

[36]  Vern Paxson,et al.  Computing TCP's Retransmission Timer , 2000, RFC.

[37]  Pasi Sarolahti,et al.  Congestion Control in Linux TCP , 2002, USENIX Annual Technical Conference, FREENIX Track.

[38]  Stefanie Gerdes,et al.  A CoAP-gateway for smart homes , 2012, 2012 International Conference on Computing, Networking and Communications (ICNC).

[39]  Hong Linh Truong,et al.  MQTT-S — A publish/subscribe protocol for Wireless Sensor Networks , 2008, 2008 3rd International Conference on Communication Systems Software and Middleware and Workshops (COMSWARE '08).

[40]  Deborah Estrin,et al.  Geography-informed energy conservation for Ad Hoc routing , 2001, MobiCom '01.

[41]  Jürgen Schönwälder,et al.  Management of resource constrained devices in the internet of things , 2012, IEEE Communications Magazine.

[42]  Ye-Qiong Song,et al.  Performance Analysis and improvement of ZigBee routing protocol , 2007 .

[43]  Stephen E. Deering,et al.  Internet Protocol, Version 6 (IPv6) Specification , 1995, RFC.

[44]  JeongGil Ko,et al.  The Trickle Algorithm , 2011, RFC.

[45]  Carsten Bormann,et al.  The Constrained Application Protocol (CoAP) , 2014, RFC.

[46]  Seong Hoon Kim,et al.  A Mesh Routing Protocol using Cluster Label in the ZigBee Network , 2006, 2006 IEEE International Conference on Mobile Ad Hoc and Sensor Systems.

[47]  Kemal Ertugrul Tepe,et al.  Design and Implementation of a Testbed for IEEE 802.15.4 (Zigbee) Performance Measurements , 2010, EURASIP J. Wirel. Commun. Netw..

[48]  Philip Levis,et al.  The nesC language: a holistic approach to networked embedded systems , 2003, SIGP.

[49]  Federico Ferrari,et al.  FlockLab: A testbed for distributed, synchronized tracing and profiling of wireless embedded systems , 2013, 2013 ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN).

[50]  Ren Wang,et al.  TCP westwood: Bandwidth estimation for enhanced transport over wireless links , 2001, MobiCom '01.

[51]  Jean-Philippe Vasseur,et al.  Terms Used in Routing for Low-Power and Lossy Networks , 2014, RFC.

[52]  Simon Heimlicher,et al.  A Survey on Routing Metrics TIK Report , 2007 .

[53]  Shuang-Hua Yang,et al.  A zigbee-based home automation system , 2009, IEEE Transactions on Consumer Electronics.

[54]  Matthias Kovatsch,et al.  Californium: Scalable cloud services for the Internet of Things with CoAP , 2014, 2014 International Conference on the Internet of Things (IOT).

[55]  Jean C. Walrand,et al.  Analysis and comparison of TCP Reno and Vegas , 1999, IEEE INFOCOM '99. Conference on Computer Communications. Proceedings. Eighteenth Annual Joint Conference of the IEEE Computer and Communications Societies. The Future is Now (Cat. No.99CH36320).

[56]  Roy Fielding,et al.  Architectural Styles and the Design of Network-based Software Architectures"; Doctoral dissertation , 2000 .

[57]  David E. Culler,et al.  TinyOS: An Operating System for Sensor Networks , 2005, Ambient Intelligence.

[58]  David L. Black,et al.  The Addition of Explicit Congestion Notification (ECN) to IP , 2001, RFC.

[59]  Stephen Dawson-Haggerty,et al.  Overview of Existing Routing Protocols for Low Power and Lossy Networks , 2009 .

[60]  Andreas Savvides,et al.  An Empirical Characterization of Radio Signal Strength Variability in 3-D IEEE 802.15.4 Networks Using Monopole Antennas , 2006, EWSN.

[61]  Feng Zhao,et al.  Scalable Information-Driven Sensor Querying and Routing for Ad Hoc Heterogeneous Sensor Networks , 2002, Int. J. High Perform. Comput. Appl..

[62]  Philip Levis,et al.  The Minimum Rank with Hysteresis Objective Function , 2012, RFC.

[63]  Hui Tian,et al.  Energy Efficient Implementation of IETF Constrained Protocol Suite , 2013 .

[64]  Adam Dunkels,et al.  Cross-Level Sensor Network Simulation with COOJA , 2006, Proceedings. 2006 31st IEEE Conference on Local Computer Networks.

[65]  Basavaraj Patil,et al.  Transmission of IPv6 Packets over BLUETOOTH Low Energy , 2013 .

[66]  Cédric Adjih,et al.  Generalized Mobile Ad Hoc Network (MANET) Packet/Message Format , 2009, RFC.

[67]  Klara Nahrstedt,et al.  On setting TCP's congestion window limit in mobile ad hoc networks , 2003, IEEE International Conference on Communications, 2003. ICC '03..

[68]  Jakob Buron,et al.  Home Automation Routing Requirements in Low-Power and Lossy Networks , 2008, RFC.

[69]  Francesca Cuomo,et al.  Routing in ZigBee: Benefits from Exploiting the IEEE 802.15.4 Association Tree , 2007, 2007 IEEE International Conference on Communications.

[70]  Anis Koubaa,et al.  Radio link quality estimation in wireless sensor networks , 2012, ACM Trans. Sens. Networks.

[71]  Carles Gomez,et al.  Wireless home automation networks: A survey of architectures and technologies , 2010, IEEE Communications Magazine.

[72]  Timo Hämäläinen,et al.  Performance analysis of IEEE 802.15.4 and ZigBee for large-scale wireless sensor network applications , 2006, PE-WASUN '06.

[73]  Srinivasan Seshan,et al.  Improving TCP/IP performance over wireless networks , 1995, MobiCom '95.

[74]  Carles Gomez,et al.  Overview and Evaluation of Bluetooth Low Energy: An Emerging Low-Power Wireless Technology , 2012, Sensors.

[75]  W. Marsden I and J , 2012 .

[76]  Yueming Hu,et al.  Issues of transport control protocols for wireless sensor networks , 2005, Proceedings. 2005 International Conference on Communications, Circuits and Systems, 2005..

[77]  H. Zimmermann,et al.  OSI Reference Model - The ISO Model of Architecture for Open Systems Interconnection , 1980, IEEE Transactions on Communications.

[78]  Mahesh K. Marina,et al.  Routing performance in the presence of unidirectional links in multihop wireless networks , 2002, MobiHoc '02.

[79]  Chieh-Yih Wan,et al.  CODA: congestion detection and avoidance in sensor networks , 2003, SenSys '03.

[80]  Carol J. Fung,et al.  Lifetime Estimation of Large IEEE 802.15.4 Compliant Wireless Sensor Networks , 2008, 2008 IEEE International Symposium on Modeling, Analysis and Simulation of Computers and Telecommunication Systems.

[81]  Philippe Jacquet,et al.  Optimized Link State Routing Protocol (OLSR) , 2003, RFC.

[82]  Godred Fairhurst,et al.  Unicast UDP Usage Guidelines for Application Designers , 2008, RFC.

[83]  Andrew T. Campbell,et al.  E-CSMA: Supporting Enhanced CSMA Performance in Experimental Sensor Networks Using Per-Neighbor Transmission Probability Thresholds , 2007, IEEE INFOCOM 2007 - 26th IEEE International Conference on Computer Communications.

[84]  Adam Dunkels,et al.  A Low-Power CoAP for Contiki , 2011, 2011 IEEE Eighth International Conference on Mobile Ad-Hoc and Sensor Systems.

[85]  Axel Colin de Verdiere,et al.  The Lightweight On-demand Ad hoc Distance-vector Routing Protocol - Next Generation (LOADng) , 2012 .

[86]  T. Braun,et al.  TCP support for sensor networks , 2007, 2007 Fourth Annual Conference on Wireless on Demand Network Systems and Services.

[87]  Philip Levis,et al.  The κ factor: inferring protocol performance using inter-link reception correlation , 2010, MobiCom.

[88]  Carsten Bormann,et al.  CoAP: An Application Protocol for Billions of Tiny Internet Nodes , 2012, IEEE Internet Computing.