Context Awareness

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Mobile ad hoc networks (MANETs) constitute an emerging communication paradigm that can potentially enable pervasive communications and computing. Their ease of deployment and the lack of centralised control make them suitable for a wide range of novel applications. On the other hand they also have drawbacks since they are characterised by a certain degree of instability, which may affect reliability and wide application deployment. As such, there is a need for techniques that mitigate these problems. In this respect, we assert that context awareness can assist in building more predictable and thus more reliable MANETs by providing higher and lower level information regarding the mobile node’s context, which can aid in predicting its mobility patterns. When the mobility of every node is predicted, the future topology of the network can be foreseen facilitating thus the construction of reliable, relatively long-lived routes. The term context is used to denote all the information accessible by the mobile node and descriptive of its surroundings whether they refer to computational or physical properties.

Aspects of this research field include:

  • Algorithms to process the diversity of context information in order to infer the future mobility patterns of the mobile nodes.
  • Extensions to ad hoc routing protocols to enable them to take into account mobility as derived from context information.
  • Context management in mobile ad hoc networks, i.e. communicating, storing and accessing context information in a scalable fashion.
  • Mobile ad hoc network programmability.
  • Enabling autonomic aspects in mobile ad hoc networks through the integration of context awareness, network programmability and policy-based network management.

This section of the Quality of Service Management Information Portal serves as a focal point for research related to context awareness in Mobile Ad Hoc Networks targeted mostly at achieving Quality of Service in this prominent networking paradigm.

General Description

The proliferation of mobile ad hoc networking solutions observed in the past few years and the high rates of user adoption regarding this technology combined with the continuously increasing number of mobile devices leads us to consider that there is paradigm shift from traditional, infrastructure networking towards a mobile, operator – free and with no fixed infrastructure type of networking, the one based in Mobile Ad Hoc Networks (MANETs). MANETs together with other emerging networking technologies, such as sensor networks, will constitute the foundations for pervasive applications such as those already envisaged by visionary researchers. The major strengths of this technology lie in the fact that it is easy to be deployed at a very low cost, while allowing for user creativity through the lack of central, authoritative management and control. The notion of pervasive computing and ubiquity are strongly correlated to that of mobile ad hoc networking technologies that thus assist in reaching innovative conceptualisations of future computing.

MANETs undoubtedly are not a panacea for every networking problem of the emerging pervasive realm. Noteworthy drawbacks include their highly dynamic topology, since every node consisting a MANET is mobile and possibly very volatile. These constant topological variations will eventually lead to a continuous state of network instability, which in turn can deteriorate the performance of services and applications on these networks. Another important issue is that typically devices participating in MANETs, have limited resources as far as storage and processing capabilities are concerned. By adding the energy constraints in the set of limitations on MANETs, one can easily understand that the road to fully grasping the potentials of ad hoc networking is not going to be an easy one.

It is obvious there is a need for techniques that mitigate these problems in order to be able to harness the vast range and diversity of enhancements and advantages that mobile ad hoc networking has to offer. In this respect context awareness can greatly assist in building and maintaining reliable, long – term MANETs. Context awareness can assist in building more predictable and thus more reliable MANETs by providing higher and lower level information regarding the mobile node’s context, which can aid in predicting its mobility patterns. When the mobility of each and every node is predicted the future topology of the network can be foreseen, allowing thus the deployment of services and facilitating scalable routing protocols. The term context is used to indicate all the information accessible by the mobile node and descriptive of its surroundings whether they refer to computational or physical properties. The driving force behind this concept is based on the observation that if one has an idea of what is happening or what is going to happen in the MANET in the near future one can act proactively and adjust the MANET in order to preserve a certain degree of network stability.

The area of context awareness and context management is a very large one, spanning across different and diverse research domains. If one attaches the notion of mobile ad hoc networking in this concept the complexity increases and one has to consider a multitude of issues when referring to context management. Attempting to identify the various aspects of context management to provide for a more systemic analysis we view the area of context management in MANETs to be classified in the following, possibly overlapping sectors.


Context sensing

This process refers to the exploitation of sensors lying scattered across an area or embedded on a mobile device to collect information on the physical or computational surroundings of the device. Open issues in this area include the discovery of available sensors that correspond to the declared preferences (what kind of information to collect being the most important) and the selection of the most appropriate sensor when there is the option of more than two available sensors.


Context gathering from sensors

This process refers to the communication and interaction with the sensors in order to gain the measurements been taken for a particular context source. Amongst the issues that need to be considered in this process, is the establishment of standardized communication with the vast diversity of sensors so as to grasp a certain degree of homogeneity in the system. The construction of generic and extensible interfaces is thus a necessity, with interfaces being able to gather different context types over different communication channels. Having identified the need for abstract interfaces to communicate with the sensors, one should not disregard the fact that no mobile node can hold all the available interfaces to all available sensors. It is therefore necessary to identify solutions to this problem by establishing an efficient and lightweight interface discovery mechanism built on top of the MANET.


Context processing

The processing of the data as received from the diversity and multitude of sensors to a standardized format is the basis of this process. Raw data as collected from the sensors have to be translated into the context model. This process is not trivial since the context model has semantic notion attached to it and raw data from sensors obviously do not. A knowledge base about the sensors and their capabilities has to be considered, with the alternative of the sensors being knowledgeable of their environment and advertising this knowledge.


Context modeling

The formalization of context information to a standard context model to serve the requirement of interoperability comprises the functionality of this process. The model should be generic enough to be capable of representing even the most complex context information, while at the same time it should not lead to large, cumbersome and highly demanding in terms of processing power structures. Interoperability should be viewed as of principal importance as well as support for semantic understanding of the modeled information.


Context sharing and distribution amongst mobile nodes

The context information available on a mobile node has to be shared and possibly distributed to the other mobile node of the MANET. The issues that arise with this process include the selection of the context to be shared and distributed across the MANET. The selection of the nodes to which the context will be distributed is an open issue, which should be considered in combination with the fact that most mobile nodes have insufficient memory resources. Also, the choice between pull-based and push-based context distribution lies as an open issue. Context distribution needs also to be viewed by another perspective, that of devices that cannot hold all of their data and need to scatter them across the MANET in other more resourceful mobile nodes.


Context semantic understanding

The information collected from sensors is not going to be useful at all if no semantic understanding of it is available, especially for predicting mobility, as is the goal of our research. The algorithms to exploit context are going to be semantic-based due to the diversity of context types. The use of ontologies should be considered, but the advanced computational requirements needed for their employment is an area to be examined beforehand.


Context discovery in the MANET

This process is correlated to that of context sharing, since it deals with the mobile nodes being able to search for and access context information stored in other mobile nodes, overcoming the MANET instability and the frequently occurring partitioning.

Publications

  • A. Dey, D. Salber, G. Abowd, "A Conceptual Framework and a Toolkit for Supporting the Rapid Prototyping of Context-Aware Applications," Human-Computer Interaction (HCI) Journal, Volume 16 (2-4), pp. 97 – 166, 2001.
  • J. Mäntyjärvi, P. Huuskonen, J. Himber, "Collaborative Context Determination To Support Mobile Terminal Applications," IEEE Wireless Communications, October 2002.
  • P. Korpipää, J. Mäntyjärvi, J. Kela, H. Keränen, E.J. Malm, "Managing Context Information in Mobile Devices," IEEE Pervasive Computing, July–September 2003.
  • A. Ranganathan, R.H. Campbell, "A Middleware for Context-Aware Agents in Ubiquitous Computing Environments," ACM/IFIP/USENIX International Conference on Middleware, 2003.
  • M. Román, C. Hess, R.Cerqueira, A. Ranganathan, R.H. Campbell, K. Nahrstedt, "A Middleware Infrastructure for Active Spaces," IEEE Pervasive Computing, pp. 74-83, October–December 2002.
  • L. Capra, W. Emmerich, C. Mascolo, "Reflective Middleware Solutions for Context-Aware Applications," In A. Yonezawa & S. Matsuoka (eds), Metalevel Architectures and Separation of Crosscutting Concerns, Proc. Of Reflection 2001, Kyoto, Japan, Lecture Notes in Computer Science, Vol. 2192, pp. 126 – 133, Springer Verlag.
  • G. Chen, D Kotz, "A Survey of Context-Aware Mobile Computing Research," Technical Report TR2000-381, Department of Computer Science, Dartmouth College, 2000.
  • G. Judd, P. Steenkiste, "Providing Contextual Information to Pervasive Computing Applications," IEEE International Conference on Pervasive Computing (PERCOM), March 2003.
  • D. Garlan, D. Siewiorek, A. Smailagic, P. Steenkiste, "Project Aura: Towards Distraction-Free Pervasive Computing," IEEE Pervasive Computing, Vol. 1, Issue 2, pp. 22–31, 2002.
  • M. Kumar, B. Shirazi, S. Das, B. Sung, D. Levine, M. Singhal, "PICO: A Middleware Framework for Pervasive Computing," IEEE Pervasive Computing, July–September 2003.
  • A. Schmidt, K. Van Laerhoven, "How to Build Smart Appliances?," IEEE Personal Communications, August 2001.
  • R. Cohen, D. Raz, "An Open and Modular Approach for a Context Distribution System," Proceedings of IEEE/IFIP Network Operations and Management Symposium (NOMS), April 2004.
  • H.G. Hegering, A. Küpper, C. Linnhoff-Popien, H. Reiser, "Management Challenges of Context-Aware Services in Ubiquitous Environments," Proceedings of the 14th IFIP/IEEE Workshop on Distributed Systems: Operations and Management (DSOM), Heidelberg, Germany, October 2003.
  • S. Chakrabarti, A. Mishra, "QoS Issues in Ad Hoc Wireless Networks," IEEE Communications Magazine, pp. 142-148, February 2001.
  • L. Blazevic, L. Buttyán, S. Giordano, J.P. Hubaux, J.Y Le Boudec, "Self-Organization in Mobile Ad Hoc Networks: The Approach of Terminodes," IEEE Communications Magazine, June 2001.
  • C. Mascolo, L. Capra, S. Zachariadis, W. Emmerich, "XMIDDLE: A Data-Sharing Middleware for Mobile Computing," Wireless Personal Communications, 21:77-103, Kluwer, 2002.
  • A.G. Ganek, T.A. Corbi, "The Dawning of the Autonomic Computing Era," IBM Systems Journal, Vol. 42, No 1, 2003.
  • R. Haas, P. Droz, B. Stiller, "Autonomic Service Deployment in Networks," IBM Systems Journal, Vol. 42, No 1, 2003.
  • D. Mandato, E. Kovacs, F. Hohl, H. Amir-Alikhani, "CAMP: A Context-Aware Mobile Portal, IEEE Communications Magazine, January 2002.
  • P. Couderc, A.M. Kermarrec, "Improving Level of Service for Mobile Users Using Context Awareness," Proceedings of 18th IEEE Symposium on Reliable Distributed Systems, Switzerland, October 1999.
  • A. Popovici, A. Frei, G. Alonso, "A Proactive Middleware Platform for Mobile Computing," ACM/I|FIP/USENIX International Conference on Middleware, 2003.
  • S.S. Yau, F. Karim, Y. Wang, B. Wang, S.K.S. Gupta, "Reconfigurable Context-Sensitive Middleware for Pervasive Computing," IEEE Pervasive Computing, July-September 2002.
  • G.C. Roman, C. Julien, Q. Huang, "Network Abstractions for Context-Aware Mobile Computing," Proceedings of 24th International Conference on Software Engineering, pp. 363-373, 2002.
  • M. Satyanarayanan, "Pervasive Computing: Vision and Challenges," IEEE Personal Communications, 2001.
  • I. Chlamtac, M. Conti, J. Liu, "Mobile Ad Hoc Networking: Imperatives and Challenges," Ad Hoc Networks 1(2003), pp. 13-64, ScienceDirect, Elsevier 2003.
  • T. Zimmer, "Towards a Better Understanding of Context Attributes," Proceedings of 2nd IEEE Annual Conference on Pervasive Computing and Communications Workshops (PERCOMW), 2004.
  • P. Korpipää, J. Mäntyjärvi, "An Ontology for Mobile Device Sensor-based Context Awareness," Proceedings Context 03, LNAI no. 2680, Springer-Verlag, pp. 451-459, 2003.
  • G. Chen, D. Kotz, "Context Aggregation and Dissemination in Ubiquitous Computing Systems," Proceedings of 4th IEEE Workshop on Mobile Computing Systems and Applications, pp. 105-114, IEEE Computer Society Press, June 2002.
  • P. Bellavista, A. Corradi, R. Montanari, C. Stefanelli, "Context-aware Middleware for Resource Management in the Wireless Internet," IEEE Transactions on Software Engineering, Vol. 29, No. 12, December 2003.
  • P. Fahy, S. Clarke, "CASS Middleware for Mobile Context-Aware Applications," ACM MobiSys 2004, Workshop on Context Awareness, June 6-9, 2004.
  • A. Chan, S.N. Chuang, "MobiPADS: A Reflective Middleware for Context-aware Mobile Computing," IEEE Transactions on Software Engineering, Vol. 29, No. 12, December 2003.
  • K. Henricksen, J. Indulska, "A Software Engineering Framework for Context-Aware Pervasive Computing," Proceedings of 2nd IEEE International Conference on Pervasive Computing and Communications (PERCOM), March 2004.
  • X. Hang Wang, D. Qing Zhang, T. Gu, H. Keng Pung, "Ontology Based Context Modeling and Reasoning using OWL," Workshop on Context Modeling and Reasoning 2004, Proceedings of the 2nd IEEE International Conference on Pervasive Computing and Communications Workshops (PERCOMW), March 2004.
  • S. Gouveris, S. Sivavakeesar, G. Pavlou, A. Malatras, "Programmable Middleware for the Dynamic Deployment of Services and Protocols in Ad Hoc Networks," Proceedings of 9th IFIP/IEEE International Symposium on Integrated Network Management (IM), May 2005.

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Dissemination

The list of journals, conferences and technical societies related to context awareness in MANETs does not mean to be exhaustive rather it is indicative. For additions/updates please contact the webmaster.

Journals

Major Conferences

Technical Societies

Software/Tools