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Mobile Agents. Martin Beer, School of Computing & Management Sciences, Sheffield Hallam University, Sheffield, United Kingdom m.beer@shu.ac.uk. Overview. Introduction to Mobile Agents What are they? How can they be used? A Currentb Example The LEAP Project The Future. Mobile Agents.
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Mobile Agents Martin Beer, School of Computing & Management Sciences, Sheffield Hallam University, Sheffield, United Kingdom m.beer@shu.ac.uk
Overview • Introduction to Mobile Agents • What are they? • How can they be used? • A Currentb Example • The LEAP Project • The Future
Mobile Agents • software processes which can: • roam wide area networks • interact with foreign hosts • perform tasks on behalf of their owners • return ‘home’
Mobile Agents:Key Hypothesis • in certain applications, they provide practical, though non-functional, advantages which escape their static counterparts “imagine having to download many images just to pick out one. Is it not more natural to get your agent to ‘go’ to that location, do a local search and only transfer the chosen compressed image back across the network?”
Host engine: requires destination place packages up the agent along with all its data, stack and instruction pointer ships it off to destination place Destination engine: unpacks agent checks its authentication agent now free to resume execution at this new place on completion of tasks, agent returns to original host The Telescript ‘go’ operation
Mobile Agents:Development Languages • Telescript • Java • Agent-Tcl • Safe-Tcl • Xlips • C/C++ • indeed any programming language
Mobile Agents:Key Challenges • transportation • authentication • secrecy and privacy • destination system security • cash • performance issues • interoperability/communication/brokering services
The LEAP Project • Acronym: Lightweight Extensible Agent Platform • Reference: IST-1999-10211 • Effort: 433.6 Man/Months • Budget: 5.4 Millions Euros • Run: Jan 2000 - June 2002 • Consortium: • Motorola (prime contractor) • ADAC • British Telecommunications • Broadcom • Telecom Italia Labs • University of Parma • Siemens
The mobile workforce • Commercial, maintenance, assistance activities are inherently mobile. • A trend which has been revolutionized by the new methods of communication (cellular phones and Internet), and which extends to new kinds of mobile workers. • Remaining issues: • Centralized management is not suited to this type of architecture; • No/limited access to information; • Expertise/Knowledge of the mobile team is under exploited; • Lack of social integration.
The LEAP objectives Develop an architecture and applications, which support a mobile enterprise workforce. • Decentralised teamwork co-ordination • Collective decision making • Flexibility in work scheduling (e.g. job swapping) • Creation of virtual teams • Travel management • Anticipating workers’ travel needs • Providing guidance and time estimation • Synchronising the movements of virtual teams • Knowledge Management • Anticipating workers’ knowledge requirements • Accessing and customising knowledge • Networking individuals with each other, based on their expertise
LEAP applications • Agent: an autonomous piece of software that acts on behalf of its user and communicates, co-operates and negotiates with its peers in order to achieve its goals. • Agents and the mobile workforce: • Some similarities (distributed, autonomous, goal driven); • Dynamic and open architecture (flexible, peer to peer); • Customize services according to users’ specific needs; • Enable emergence of intelligent behaviours. • Generic services: swap-shift, plan-route, make-collective-decision, find-expert… • JADE-LEAP a standard agent platform that runs on devices from phones to PDA to desktops.
BT Technical scenario Jobs DB Specific work request Selection of Field Engineer based on personal preferences Work Scheduler Customer Repair fault Information (Expert, Technical) Update (Experience) Geogr. DB Travel to Job Guidance (Route planning) Information (Traffic) Field Engineer Find-relevant-information Find-expert Plan-route Traffic Expertise DB Update-knowledge Find-relevant-information Estimate-route-cost
D C B A Social scenario Social Events DB Geogr. DB Jobs DB Field Engineer Field Engineer Trade work (Shifts, Holidays, Overtime) Organize meetings (Event, Location, Time) Field Engineer Plan-route Swap-shift Field Engineer Make-collective-decision Coordinate-social-activity
Field trials ADAC - Yellow Angel Trial ADAC employs 1,700 “Yellow Angels” for road-side assistance in Germany performing 9600 incidents / repair cases per day while driving 150,000 km. Time: March-April 2002, duration 10 days Localition: area of 100 km around Munich, Germany Participants: 5 yellow angels (in shifts, more than 2 per shift) How: Emulate several car breakdowns per day BT - Field Engineer Trial BT has 25,000 engineers performing 150,000 installation and repair tasks each day in the UK. Time: March-April 2002, duration 14 days Localition: area of Birmingham, UK Participants: 10 Customer Service Team members (more than 2 per field unit to have some social interaction) How: Parallel working with current and LEAP systems within real work situations
What was Achieved? • Achievements: • A FIPA compliant agent platform that runs on all Java editions (J2SE, J2ME, pJava, J1.1.x). Released in open-source on September 26th, 2001; • Validation of concept on a laboratory trial application: the cinema-organizer; • Won the System Innovation Award at CIA’01 workshop, demonstrating the cinema-organizer on Accompli008 through GSM and iPAQ through WaveLAN. • Next challenges: • Complete applications (Integration of generic services, legacy systems and databases) • Heavy testing of the applications • Prepare training and evaluation materials (user documentation, interviews) • Run the field trials • Evaluate the field trials
The future… • Agentcities.RTD and Agentcities.NET, two new European projects deploying a worldwide network of agent platforms. • A lot of spin-off projects. • Active research concerns: • Security, trust and privacy; • Ontology sharing; • Service clustering; • Integration with m-Commerce; • From specialization to personalization; • Social and cultural impacts. London Ipswich Paris Berlin Dublin Saarbruecken Montpellier Sendai Lausanne San Francisco Lisbon Parma Barcelona