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Self-Adaptive, Decentralised Data Publication over Wireless
Networks
Richard Cooksey
Supervisor: Prof. A. Taleb-Bendiab
Introduction
• Many wireless communication technologies to enable short-range communications between devices such as WiFi, Bluetooth, and UWB
• Interest in extending these by nodes co-operatively message passing.
• Many possible applications of this concept/algorithm with varying requirements and placing different demands on a 'would be' solution.
Current Ideas for ad-hoc wireless
• Reactive protocols have no real idea where they are until they have a need to pass a message to another node
• Proactive protocols regularly announce their presence to each other, and tell other nodes about their surroundings, so that a node has a ‘picture’ of where it is in the network that is refreshed at intervals.
• Hybrid approaches• Hardware assisted protocols – such as
requiring GPS
Example Usage ScenariosSensor Network
• Static network topology• All devices ‘equal’• Fairly evenly spaced• Small amounts of data at
regular intervals
Example Usage ScenariosGroup working
• Build node familiarity• Networking with
irrelevant devices is wasteful
Example Usage ScenariosClustered Groups of Devices
• Mobile team-working situation
• Different device types with different constraints (power, range, etc)
• Use of ‘gateways’
Adaptability to different usage scenarios
• Automatically attempt to maximise efficiency despite conflicting goals
• ‘Generic’ algorithm/protocol with sufficient adaptability to be relatively efficient regardless of appliance
Desirable Attributes
• Node/Service awareness
• Integration with other longer-range wireless technologies such as 3G and use of fixed infrastructure where available
• Information boundaries - restricting message propagation within a structure, or within a certain distance from source
• Location awareness
Service-based
• Services ‘published’ by their service description propagating outwards from source to desired audience
• Easy to send to host, and path constructed en route for reply
Measured Approach
• Possible use of ‘coincidental’ data to aid routing through concept of location, distance, and movement rate?
• Signal strength an aid in tracking node movement for routing path repair?
• Use of different radio frequencies to determine physical boundaries?
Adaptability
• Taking advantage of periods of stability to reduce communication overhead (such as polling interval)
• Change parameters such as power output (transmission distance) based on surroundings (node density, level of interference)
• Modes of operation? Work differently when user is ‘sleeping’, ‘working’, ‘stationary’, ‘in motion’ etc.
• Form ‘relationships’, group together, and elect leaders
Summary
• Great deal of interest in this area
• No ‘perfect’ solution, ideas require simulating and testing.
• Many possible uses
• Gaps in current ideas have been identified and solutions proposed
References• [Epidemic-style Protocls] Gupta, I.;Kermarrec, AM.;Ganesh, A.; “Efficient
Epidemic-style Protocols for Reliable and Scalable Multicast”, Dept. of Computer Science, Cornell University, Ithaca, NY USA, April 2002
• [Associativity-Based Routing for Ad-Hoc Mobile Networks] Toh, CK.; “Associativity-Based Routing For Ad-Hoc Mobile Networks”, University of Cambridge Computer Laboratory, Cambridge, 1996
• [Broadcasting for Mobile Ad Hoc Networks] Willaims, B.; “Network Wide Broadcasting Protocols for Mobile Ad Hoc Networks”, Colorado School of Mines, 2002
• [Broadcast Storm] Tseng, YC.; Ni, SY.; Chen, YS.; Sheu, JP.; “The Broadcast Storm Problem in a Mobile Ad Hoc Network”, Department of Computer Science and Information Engineering, National Chiao-Tung University, Feb 2001
• [Wireless Networking Roundup] “Wireless Networking Roundup: Ricochet, Bluetooth and IEEE 802.11b”, http://www.dansdata.com/wireless.htm, January 2003
• [Ultra-wideband] Kelland, B.; “Ultra-wideband wireless technology”, University of Southampton: Department of Electronics and Computer Science, December 2002