System support for spontaneous pervasive computing environments

Mobile networked devices become more and more pervasive. By embedding such devices into everyday items, pervasive computing systems will emerge in the near future. Current approaches for such systems are based on the model of Smart Environments. In such environments, a preinstalled hardware infrastructure enhances a spatial area, e.g., a room or house, and enables it to coordinate multiple mobile devices present in the environment to cooperatively provide services to the users. However, such systems rely on the presence of such an expensive infrastructure and do not work in areas without it. This restricts the deployment of pervasive computing systems severely. Therefore, in this work we propose another model for pervasive computing systems, the so-called Smart Peer Group model. A Smart Peer Group consists of a number of interconnected mobile devices that discover each other dynamically and form a spontaneous composition of devices. Coordination is provided by the participating devices themselves and no external infrastructure is needed. This results in a highly flexible system that can be used at any time and anywhere. The development of such systems is a non trivial task, due to the high level of dynamism, the potentially high resource constraintness, and the unpredictable nature of Smart Peer Groups. In this dissertation, we present the Smart Peer Group model and analyze the specific characteristics of this system class. In addition, we propose a number of concepts and algorithms to develop Smart Peer Group-based Pervasive Computing systems. A communication middleware for Smart Peer Groups is presented, which offers means to cope with resource-poor specialized devices and shields application developers from fluctuating network connectivities. Furthermore, a service discovery system for such systems is developed, which allows unused devices to temporarily deactivate themselves in order to save energy without loosing the ability to discover new services or to be discovered by others. The presented concepts and algorithms are evaluated in different scenarios using an analytical and an experimental evaluation. Mit der zunehmenden Verbreitung immer leistungsstarkerer und kompakterer mobiler Rechnersysteme durchdringen diese unsere alltagliche Umgebung immer mehr. Mittelfristig ist davon auszugehen, dass Anwender immer und uberall von einer Vielzahl elektronischer Gerate umgeben sein werden, die mittels drahtloser Kommunikation miteinander kooperieren. Gerate konnen hierbei fur den Anwender unsichtbar in Gegenstande des taglichen Bedarfs eingebettet oder in die Umgebung integriert sein. Ein solches System wird als ubiquitares Rechnersystem bezeichnet. Bei der Entwicklung ubiquitarer Rechnersysteme wurde in der Vergangenheit stark auf sogenannte intelligente Umgebungen, d.h. elektronisch erweiterte Umgebungen, fokussiert. Hierbei wird in einem eingegrenzten raumlichen Gebiet, z.B. einem Zimmer oder einem Haus, eine geeignete Infrastruktur installiert, die es den im Gebiet vorhandenen Geraten erlaubt, miteinander zu kooperieren. Dieses Architekturmodell erfordert es, vor dem Betrieb des Systems eine geeignete Systeminfrastruktur in Form von Hardware und Software im antizipierten Betriebsumfeld zu installieren. Dies ist mit hohen Investitionskosten verbunden und schrankt die Verwendbarkeit ubiquitarer Systeme auf vorgegebene raumliche Gebiete ein. In dieser Arbeit wird ein alternatives Architekturmodell fur ubiquitare Rechnersysteme entwickelt, das keine externe Infrastruktur benotigt und auf dem Konzept der sogenannten spontanen Funktionsverbunde beruht. Nach einer Analyse der Herausforderungen, die bei der Entwicklung spontaner Funktionsverbunde auftreten, werden im weiteren Verlauf der Arbeit Verfahren, Konzepte und Algorithmen vorgestellt mit denen diese Herausforderungen uberwunden werden konnen und eine effiziente und flexible Koordination der Gerate eines spontanen Funktionsverbundes ermoglicht wird. Hierzu wird zum einen ein Konzept entwickelt, mit dem eine Flexibilisierung der Geratekommunikation ermoglicht wird, indem das Kommunikationsmodell einer Anwendung vom Synchronisationsmodell der verwendeten Interoperabilitatsprotokolle entkoppelt wird. Zudem wird eine strategiebasierte dynamische Auswahl der verwendeten Kommunikationsprotokolle vorgeschlagen, mittels derer eine fortlaufende Anpassung des Kommunikationssystems an Wechsel in der Ausfuhrungsumgebung ermoglicht wird. Diese Konzepte werden in eine mikrokernbasierte Verteilungsinfrastruktur integriert, die fur ressourcenbeschrankte Gerate entwickelt wurde. Im zweiten Teil der Arbeit werden Verfahren zur dynamischen Erkennung der aktuellen Anwendungsumgebung untersucht und ein Verfahren zur energieeffizienten Erkennung entfernter Dienste und Gerate auf Basis eines Gruppierungsalgorithmus vorgeschlagen.

[1]  Tei-Wei Kuo,et al.  Energy-efficient flash-memory storage systems with an interrupt-emulation mechanism , 2004, International Conference on Hardware/Software Codesign and System Synthesis, 2004. CODES + ISSS 2004..

[2]  Daniel McKenna Mobile Platform Benchmarks A Methodology for Evaluating Mobile Computing Devices , 2000 .

[3]  Gregor Schiele,et al.  BASE - a micro-broker-based middleware for pervasive computing , 2003, Proceedings of the First IEEE International Conference on Pervasive Computing and Communications, 2003. (PerCom 2003)..

[4]  Deborah Estrin,et al.  Topology Control Protocols to Conserve Energy in Wireless Ad Hoc Networks , 2003 .

[5]  Fabio Kon,et al.  Reflective Middleware: From Your Desk to Your Hand , 2001, IEEE Distributed Syst. Online.

[6]  Dirk Husemann,et al.  DEAPspace-transient ad-hoc networking of pervasive devices , 2000, 2000 First Annual Workshop on Mobile and Ad Hoc Networking and Computing. MobiHOC (Cat. No.00EX444).

[8]  Giovanni De Micheli,et al.  Software controlled power management , 1999, CODES '99.

[9]  Michael B. Jones,et al.  Mach: a system software kernel , 1989, Digest of Papers. COMPCON Spring 89. Thirty-Fourth IEEE Computer Society International Conference: Intellectual Leverage.

[10]  Martin Nilsson,et al.  Investigating the energy consumption of a wireless network interface in an ad hoc networking environment , 2001, Proceedings IEEE INFOCOM 2001. Conference on Computer Communications. Twentieth Annual Joint Conference of the IEEE Computer and Communications Society (Cat. No.01CH37213).

[11]  Karsten Sohr,et al.  Pini - A Jini-Like Plug&Play Technology for the KVM/CLDC , 2001, IICS.

[12]  M. Frans Kaashoek,et al.  Mobile Computing with the Rover Toolkit , 1997, IEEE Trans. Computers.

[13]  M. Roman,et al.  Design and implementation of runtime reflection in communication middleware: the dynamicTAO case , 1999, Proceedings. 19th IEEE International Conference on Distributed Computing Systems. Workshops on Electronic Commerce and Web-based Applications. Middleware.

[14]  Gregor Schiele,et al.  ContextCube - providing context information ubiquitously , 2003, 23rd International Conference on Distributed Computing Systems Workshops, 2003. Proceedings..

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

[16]  Krishna M. Sivalingam,et al.  A Survey of Energy Efficient Network Protocols for Wireless Networks , 2001, Wirel. Networks.

[17]  Rafal A. Angryk MICO, An Open Source CORBA Implementation , 2001, Scalable Comput. Pract. Exp..

[18]  Dirk Husemann,et al.  DEAPspace: transient ad-hoc networking of pervasive devices , 2000, MobiHoc.

[19]  Robert Tappan Morris,et al.  Span: An Energy-Efficient Coordination Algorithm for Topology Maintenance in Ad Hoc Wireless Networks , 2001, MobiCom '01.

[20]  Anantha P. Chandrakasan,et al.  An application-specific protocol architecture for wireless microsensor networks , 2002, IEEE Trans. Wirel. Commun..

[21]  Paramvir Bahl,et al.  Wake on wireless: an event driven energy saving strategy for battery operated devices , 2002, MobiCom '02.

[22]  Deborah Estrin,et al.  Adaptive energy conservation protocols for wireless ad hoc routing , 2002 .

[23]  Umar Saif,et al.  A Case for Goal-oriented Programming Semantics , 2003 .

[24]  Massoud Pedram,et al.  Dynamic power management based on continuous-time Markov decision processes , 1999, DAC '99.

[25]  Cheng Wang,et al.  Impact of data compression on energy consumption of wireless-networked handheld devices , 2003, 23rd International Conference on Distributed Computing Systems, 2003. Proceedings..

[26]  David Garlan,et al.  Project Aura: Toward Distraction-Free Pervasive Computing , 2002, IEEE Pervasive Comput..

[27]  Charles E. Perkins,et al.  Service Location Protocol, Version 2 , 1999, RFC.

[28]  Guy Eddon,et al.  Inside Distributed COM , 1998 .

[29]  Michael Nidd Reducing Power Use in DEAPspace Service Discovery , .

[30]  Amin Vahdat,et al.  Currentcy: A Unifying Abstraction for Expressing Energy Management Policies , 2003, USENIX Annual Technical Conference, General Track.

[31]  A. Ephremides,et al.  A design concept for reliable mobile radio networks with frequency hopping signaling , 1987, Proceedings of the IEEE.

[32]  M. Weiser The Computer for the Twenty-First Century , 1991 .

[33]  Albrecht Schmidt,et al.  There is more to context than location , 1999, Comput. Graph..

[34]  Gregor Schiele,et al.  Experience using Processes for Pervasive Applications , 2006, GI Jahrestagung.

[35]  Deborah Estrin,et al.  An energy-efficient MAC protocol for wireless sensor networks , 2002, Proceedings.Twenty-First Annual Joint Conference of the IEEE Computer and Communications Societies.

[36]  Reginald Ferber,et al.  Information Retrieval - Suchmodelle und Data-Mining-Verfahren für Textsammlungen und das Web , 2003 .

[37]  Martha Steenstrup,et al.  Cluster-based networks , 2001 .

[38]  J. Flinn,et al.  Energy-aware adaptation for mobile applications , 1999, SOSP.

[39]  Mahadev Satyanarayanan,et al.  Extending mobile computer battery life through energy-aware adaptation , 2001 .

[40]  S. M. Heemstra de Groot,et al.  Power-aware routing in mobile ad hoc networks , 1998, MobiCom '98.

[41]  Armando Fox,et al.  The Interactive Workspaces Project: Experiences with Ubiquitous Computing Rooms , 2002, IEEE Pervasive Comput..

[42]  Alan Jay Smith,et al.  Software strategies for portable computer energy management , 1998, IEEE Wirel. Commun..

[43]  Robbert van Renesse,et al.  The Amoeba distributed operating system - A status report , 1991, Comput. Commun..

[44]  Gregor Schiele,et al.  Supporting Pluggable Configuration Algorithms in PCOM , 2007, Fifth Annual IEEE International Conference on Pervasive Computing and Communications Workshops (PerComW'07).

[45]  Christian Becker,et al.  A framework for re-use and maintenance of Quality of Service mechanisms in distributed object systems , 2001, Proceedings IEEE International Conference on Software Maintenance. ICSM 2001.

[46]  Luca Benini,et al.  System-level power estimation and optimization , 1998, Proceedings. 1998 International Symposium on Low Power Electronics and Design (IEEE Cat. No.98TH8379).

[47]  Jonne Soininen GPRS and UMTS release 2000 A11-IP option , 2000, MOCO.

[48]  Gordon S. Blair,et al.  An architecture for next generation middleware , 2009 .

[49]  C C. Chiang,et al.  Routing in Clustered Multihop, Mobile Wireless Networks With Fading Channel , 1997 .

[50]  Carla Schlatter Ellis,et al.  The case for higher-level power management , 1999, Proceedings of the Seventh Workshop on Hot Topics in Operating Systems.

[51]  Gregor Schiele,et al.  Middleware and application adaptation requirements and their support in pervasive computing , 2003, 23rd International Conference on Distributed Computing Systems Workshops, 2003. Proceedings..

[52]  Gregor Schiele,et al.  Energy-efficient cluster-based service discovery for Ubiquitous Computing , 2004, EW 11.

[53]  P.H.J. Chong,et al.  A survey of clustering schemes for mobile ad hoc networks , 2005, IEEE Communications Surveys & Tutorials.

[54]  Michael H. Coen,et al.  Meeting the Computational Needs of Intelligent Environments: The Metaglue System , 2000 .

[55]  Christian Becker,et al.  Generic QoS-support for CORBA , 2000, Proceedings ISCC 2000. Fifth IEEE Symposium on Computers and Communications.

[56]  Roy H. Campbell,et al.  Unified Object Bus: Providing Support for Dynamic Management of Heterogeneous Components , 2001 .

[57]  Michael C. Mozer,et al.  The Neural Network House: An Environment that Adapts to its Inhabitants , 1998 .

[58]  Roy H. Campbell,et al.  Gaia: enabling active spaces , 2000, ACM SIGOPS European Workshop.

[59]  Prithwish Basu,et al.  A mobility based metric for clustering in mobile ad hoc networks , 2001, Proceedings 21st International Conference on Distributed Computing Systems Workshops.

[60]  David S. Johnson,et al.  Computers and Intractability: A Guide to the Theory of NP-Completeness , 1978 .

[61]  Andy Hopper,et al.  Implementing a Sentient Computing System , 2001, Computer.

[62]  Luca Benini,et al.  Quantitative comparison of power management algorithms , 2000, Proceedings Design, Automation and Test in Europe Conference and Exhibition 2000 (Cat. No. PR00537).

[63]  Nathan Ickes,et al.  Physical layer driven protocol and algorithm design for energy-efficient wireless sensor networks , 2001, MobiCom '01.

[64]  Krishna M. Sivalingam,et al.  Performance comparison of battery power consumption in wireless multiple access protocols , 1999, Wirel. Networks.

[65]  Baochun Li,et al.  Group mobility and partition prediction in wireless ad-hoc networks , 2002, 2002 IEEE International Conference on Communications. Conference Proceedings. ICC 2002 (Cat. No.02CH37333).

[66]  Inseok Choi,et al.  Low-power color TFT LCD display for hand-held embedded systems , 2002, Proceedings of the International Symposium on Low Power Electronics and Design.

[67]  Armando Fox,et al.  Portability, extensibility and robustness in iROS , 2003, Proceedings of the First IEEE International Conference on Pervasive Computing and Communications, 2003. (PerCom 2003)..

[68]  Roy H. Campbell,et al.  Integrating PDAs into Distributed Systems: 2K and PalmORB , 1999, HUC.

[69]  Don Loomis The TINI specification and developer's guide , 2001 .

[70]  Krishna M. Sivalingam,et al.  Design and analysis of low‐power access protocols for wireless and mobile ATM networks , 2000, Wirel. Networks.

[71]  Robert Grimm,et al.  Programming for Pervasive Computing Environments , 2001 .

[72]  Mark Weiser,et al.  Some computer science issues in ubiquitous computing , 1999, MOCO.

[73]  Roberto Chinnici,et al.  Web Services Description Language (WSDL) Version 2.0 Part 1: Core Language , 2007 .

[74]  Gregor Schiele,et al.  PCOM - a component system for pervasive computing , 2004, Second IEEE Annual Conference on Pervasive Computing and Communications, 2004. Proceedings of the.

[75]  T. Nixon,et al.  Home networking with Universal Plug and Play , 2001 .

[76]  Scott Shenker,et al.  Scheduling for reduced CPU energy , 1994, OSDI '94.

[77]  Yu-Chee Tseng,et al.  Power-saving protocols for IEEE 802.11-based multi-hop ad hoc networks , 2003, Comput. Networks.

[78]  Xiaoyan Hong,et al.  A group mobility model for ad hoc wireless networks , 1999, MSWiM '99.

[79]  Randy H. Katz,et al.  Measuring and Reducing Energy Consumption of Network Interfaces in Hand-Held Devices (Special Issue on Mobile Computing) , 1997 .

[80]  Luca Benini,et al.  Event-driven power management of portable systems , 1999, Proceedings 12th International Symposium on System Synthesis.

[81]  Suresh Singh,et al.  PAMAS—power aware multi-access protocol with signalling for ad hoc networks , 1998, CCRV.

[82]  Michael Nidd,et al.  Service discovery in DEAPspace , 2001, IEEE Wirel. Commun..

[83]  Hari Balakrishnan,et al.  The design and implementation of an intentional naming system , 1999, SOSP.

[84]  Gregory D. Abowd,et al.  The Aware Home: A Living Laboratory for Ubiquitous Computing Research , 1999, CoBuild.

[85]  A.E. Kamal,et al.  Data aggregation in wireless sensor networks - exact and approximate algorithms , 2004, 2004 Workshop on High Performance Switching and Routing, 2004. HPSR..

[86]  Carl Staelin,et al.  Idleness is Not Sloth , 1995, USENIX.

[87]  Vincent Lenders,et al.  Mini : A Minimal Platform Comparable to Jini for Ubiquitous Computing , 2002 .

[88]  Mario Gerla,et al.  Multicluster, mobile, multimedia radio network , 1995, Wirel. Networks.

[89]  Luca Benini,et al.  System-level power optimization: techniques and tools , 1999, ISLPED '99.

[90]  Sharad Malik,et al.  Instruction level power analysis and optimization of software , 1996, Proceedings of 9th International Conference on VLSI Design.

[91]  Steve Mann Smart clothing: The wearable computer and wearcam , 2005, Personal Technologies.

[92]  Gregor Schiele,et al.  Adaptation Support for Stateful Components in PCOM , 2005 .