Dynamic software update model for remote entity management of machine-to-machine service capability

Daily life applications of machine-to-machine (M2M) communication are constantly increasing. Typically, M2M communication systems comprise numerous small, cheap and autonomous devices that communicate with each other while monitoring environmental conditions. After their deployment, however, remote entity management of a node is still needed for firmware or software updates required for bug fixes, functional changes or other maintenance. Therefore implementing remote entity management for M2M service capability in third generation partnership project machine-type-communication is a major challenge. Previous works have attempted to reduce traffic by updating only the software changes in the M2M device. However, the device must still reboot after a software update. Rebooting the device is costly since the previous runtime states are lost. The devices expend time and bandwidth when synchronising with other nodes and when rebuilding the routing table. Hence, the dynamic software update model (DSUM) proposed in this study is designed to enable remote entity management for M2M. A dynamic software update programming model and a prototype implementation for M2M service capability are also presented. By allowing M2M service capabilities to update the software without rebooting the node, the DSUM preserves precious runtime states. The tests in this study showed that software updating required only 88 clock cycles. This framework not only enables dynamic replacement of remote entity management functionalities at runtime, it also reduces power consumption by avoiding the need to rebuild the network topology for devices in an M2M communication network.

[1]  Roy Shea,et al.  Sensor network software update management: a survey , 2005 .

[2]  J. W. Hunt,et al.  An Algorithm for Differential File Comparison , 2008 .

[3]  Xiaohui Liang,et al.  Securing smart grid: cyber attacks, countermeasures, and challenges , 2012, IEEE Communications Magazine.

[4]  Paul Mackerras,et al.  The rsync algorithm , 1996 .

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

[6]  Hung-Yu Wei,et al.  Lte-advanced and 4g Wireless Communications: Part 2 Overload Control for Machine-type-communications in Lte-advanced System Rach Procedure Signaling Flow Ue Behaviors Ran Overload Control Method , 2022 .

[7]  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.

[8]  Kien A. Hua,et al.  An Efficient Broadcast Technique for Vehicular Networks , 2011, J. Inf. Process. Syst..

[9]  Robert W. Sebesta,et al.  Concepts of programming languages , 1973 .

[10]  Ralph Johnson,et al.  design patterns elements of reusable object oriented software , 2019 .

[11]  Konstantinos N. Plataniotis,et al.  Green modulations in energy-constrained wireless sensor networks , 2010, IET Commun..

[12]  Der-Jiunn Deng,et al.  A Collision Alleviation Scheme for IEEE 802.11p VANETs , 2011, Wirel. Pers. Commun..

[13]  Jun Zheng,et al.  Rate-constrained uniform data collection in wireless sensor networks , 2011, IET Commun..

[14]  Philip Levis,et al.  Surviving sensor network software faults , 2009, SOSP '09.

[15]  Deborah Estrin,et al.  A Remote Code Update Mechanism for Wireless Sensor Networks , 2003 .

[16]  Bong Wan Kim,et al.  An efficient remote code update mechanism for Wireless Sensor Networks , 2009, MILCOM 2009 - 2009 IEEE Military Communications Conference.

[17]  Jeff Rose,et al.  MANTIS: system support for multimodAl NeTworks of in-situ sensors , 2003, WSNA '03.

[18]  Deborah Estrin,et al.  The Tenet architecture for tiered sensor networks , 2006, SenSys '06.

[19]  Lida Xu,et al.  The internet of things: a survey , 2014, Information Systems Frontiers.

[20]  Marvin Theimer,et al.  Cooperative Task Management Without Manual Stack Management , 2002, USENIX Annual Technical Conference, General Track.

[21]  David E. Culler,et al.  Incremental network programming for wireless sensors , 2004, SECON.

[22]  Liang Zhou,et al.  Optimization architecture for joint multi-path routing and scheduling in wireless mesh networks , 2011, Math. Comput. Model..

[23]  Adam Dunkels,et al.  Run-time dynamic linking for reprogramming wireless sensor networks , 2006, SenSys '06.

[24]  Naixue Xiong,et al.  Design and Analysis of Self-Adapted Task Scheduling Strategies in Wireless Sensor Networks , 2011, Sensors.

[25]  Han-Chieh Chao,et al.  Robust Header Compression with Load Balance and Dynamic Bandwidth Aggregation Capabilities in WLAN , 2007 .

[26]  Philip Levis,et al.  Maté: a tiny virtual machine for sensor networks , 2002, ASPLOS X.

[27]  Joel J. P. C. Rodrigues,et al.  Data fusion on wireless sensor and actuator networks powered by the zensens system , 2011, IET Commun..

[28]  Han-Chieh Chao,et al.  Jumping ant routing algorithm for sensor networks , 2007, Comput. Commun..

[29]  Theodore S. Rappaport,et al.  Short-Range Wireless Communications for Next-Generation Networks: UWB, 60 GHz Millimeter-Wave WPAN, And ZigBee , 2007, IEEE Wireless Communications.

[30]  Yueh-Min Huang,et al.  Constructing secure group communication over wireless ad hoc networks based on a virtual subnet model , 2007, IEEE Wireless Communications.

[31]  Joel Koshy,et al.  Remote incremental linking for energy-efficient reprogramming of sensor networks , 2005, Proceeedings of the Second European Workshop on Wireless Sensor Networks, 2005..

[32]  Deborah Estrin,et al.  Directed diffusion: a scalable and robust communication paradigm for sensor networks , 2000, MobiCom '00.

[33]  Marimuthu Palaniswami,et al.  Spatio-temporal modelling-based drift-aware wireless sensor networks , 2011, IET Wirel. Sens. Syst..

[34]  Gang Liu,et al.  Relay node placement based on balancing power consumption in wireless sensor networks , 2011, IET Wirel. Sens. Syst..

[35]  Mani B. Srivastava,et al.  Sensor network software update management: a survey , 2005, Int. J. Netw. Manag..

[36]  Koen Langendoen,et al.  Efficient code distribution in wireless sensor networks , 2003, WSNA '03.