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Load Balancing using Mobile Agent Approach
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  1. Load Balancing using Mobile Agent Approach Prepared by: Wong Tsz Yeung,Ah Mole Supervisor : Prof. Michael Lyu 18 December 2000

  2. Introduction (1) • Autonomous Agents • 2 kinds of research going on : • Multi-Agent System; and • Mobile Agent • How do they different?? • What are the advantages and disadvantages of using them??

  3. Introduction (2) • Parallel Computing • Load Balancing • In the past - Super Computer with multi-processor • Nowadays - Cluster of Single of multi-processor machines • Can we build a system that combine the advantages of agent and load balancing??

  4. Multi-Agent System (MAS) (1) • The goal of MAS : • Creating a system that interconnects separately developed agents, thus enabling the ensemble to function beyond the capabilities of any singular agent in the system. • Implication: Specialization on agents.

  5. Multi-Agent System (MAS) (2) • Every Agent is specialized to perform particular task. • To perform a task, an agent that is onbehalf of the user need to communicate with one or more agents in order to complete a task.

  6. Multi-Agent System (MAS) (3) • All the agents in a MAS can be provided by one by more venders given that: • Agents are using the same language in communication. • Agents are having the same kind of knowledge.

  7. Multi-Agent System (MAS) (4) • For Example: • A business from US wants to arrange a trip from New York to Hong Kong. • He has to plan: • Which airline will he take?? • Which hotel will he stay??

  8. Multi-Agent System (MAS) (5) • Fortunately, the business man has a personal agent. • i.e. his secretary • Then, the secretary phones the airline companies and hotels for information.

  9. Multi-Agent System (MAS) (6) • She can make a final decision based on the criteria given by her boss. • E.g. • Choose the cheapest airline. • Choose the most comfortable hotel. • The above case shows how human agents work.

  10. user Multi-Agent System (MAS) (7) • We can treat the above case as: Airline Agent 1 Airline Agent 2 Agent Hotel Agent 1 Hotel Agent 2

  11. Multi-Agent System (MAS) (8) • Advantages • Technically speaking • It is autonomous in the sense that the agent can find a service provider, query for suitable information and determine the final result. • Every service provider has its own implementation. However, it is transparent to the user agent.

  12. Multi-Agent System (MAS) (9) • Economically speaking • Every agent is specialized, so it can sell the service. User can buy the service which meets he/she criteria.

  13. Challenges in MAS (1) • Information Discovery Problem • Human Agent : Go to Yahoo! to search for the related information. • How can software agent locate other agents??

  14. Return a list of name of service provider. Searching for service provider. Discovery server Successfully locate a service provider. Lookup the address of a service provider. Lookup server Challenges in MAS (2) Service-seeking agent service provider

  15. Challenges in MAS (3) • The Discover server provides yellow page service. • The Lookup server provides white page service. • Jini also has such discovery-and-lookup mechanism.

  16. Challenges in MAS (4) • Communication Problem • It is the communication language problem. • E.g. On the Internet, we have HTML which is widely used. • An agent-to-agent language is more preferable. • KQML - Knowledge Query Markup Language. • ACL - Agent Communication Language from FIPA.

  17. Challenges in MAS (5) • Ontology Problem • It is problem dealing with the context of the communication language. • E.g. Bus has a meaning in the transportation field while it is different in computer field. • The agents involved in a MAS must agree on and share a common definition of concepts.

  18. Challenges in MAS (6) • This problem hinders the development of agent interoperability. • Systems tend to use their own knowledge database. • we cannot plug another agent into the current existing MAS, unless we are using the same knowledge base.

  19. Mobile Agent (MA) (1) • The goal of Mobile Agent • You delegate tasks to an agent. The agent will do the tasks for you. • Instead of passing message among agents, mobile agent can migrate across the network (hence mobile) representing users in various tasks (hence agents).

  20. Mobile Agent (MA) (2) • Potential application domains of MA • Data-intensive application. • Disconnected computing. • However, the sad fact is • there is no application that would not exist without mobile agents. • Every mobile agent application will have its client-server counterpart such as RPC or sockets.

  21. Mobile Agent (MA) (3) • The difference between MA and MAS • They have similar properties. • Mobile agent can migrate itself to other hosts.

  22. Machine A Machine B Machine C Load Balancing (1) • Imagine that you are inside a factory : • Our Goal : to minimize the total length of time needed to process a fixed set of tasks. ? ? ?

  23. Load Balancing (2) • Our approach is a greedy approach. • Whenever a new job comes in the system, we search for the machine that has the minimum load. • We assign the new job to the minimum-load machine.

  24. where is mapping that maps T to real number >= 0 Description of the System (1) • Suppose we are given: • n identical processing units, namely Pi where 1 <= i <= n • A set of tasks: T = {T1, T2, …, Tm} • A partial-order < on T and a function

  25. Description of the System (2) • Once a processor Pi begins a task Tj, It works without interruption on Tj until completion • The time that is taken : (Tj). • If Ti < Tj, Tj cannot be started until Ti is completed.

  26. Description of the System (3) • Pi executes the task Tj in the following way: • We are given a linear ordering • L is called a task list. • In any time t, a Pi completes a task, it immediately scans the list L. L : (Tk1, …, Tkm)

  27. Description of the System (4) • Pi scans from the beginning of L until it comes to the first task Tjwhich has not yet begun to be executed. • If Ti < Tj and Ti has been finished, Pi begins to executes Tj. • Otherwise, Pi proceeds to the next task in L which has not begun executing.

  28. Description of the System (5) • If Pi proceeds through the entire list L without finding a task to execute, then Pi becomes idle. • Idle means Pi is executing an empty task. • Pi remains idle until some other Pj completes a task.

  29. Description of the System (6) • At that time, Pi immediately scans the list L as before for possible tasks to execute. • If Pi and Pj, i < j, simultaneously attempt to begin the same task Tk, the processor with the smaller index will execute Tk, i.e. Pi.

  30. Description of the System (7) • The processors all start scanning L at time t = 0 and proceed in the above-mentioned fashion until some time w. • Our aim is to minimize w.

  31. T1/4 T2/3 T4/5 T3/1 T5/3 T6/2 T7/2 T8/3 Description of the System (8) • E.g. 1. • n = 3 • L : (T3, T1, T2, T4, T6, T5, T7, T8) • Partial relation :

  32. P1 T1/4 T2/3 P2 T4/5 T3/1 T5/3 P3 T8/3 T6/2 T7/2 Description of the System (9) • E.g 1 (continued) T1 T2 E1 4 3 2 T4 T3 T5 5 1 3 T6 T7 T8 E2 2 2 3 2 L : (T3, T1, T2, T4, T6, T5, T7, T8) L : (T3, T1, T2, T4, T6, T5, T7, T8) L : (T3, T1, T2, T4, T6, T5, T7, T8) L : (T3, T1, T2, T4, T6, T5, T7, T8) L : (T3, T1, T2, T4, T6, T5, T7, T8) L : (T3, T1, T2, T4, T6, T5, T7, T8) L : (T3, T1, T2, T4, T6, T5, T7, T8) L : (T3, T1, T2, T4, T6, T5, T7, T8) L : (T3, T1, T2, T4, T6, T5, T7, T8)

  33. Description of the System (13) • E.g. 3

  34. Description of the System (14) • From the above observations, we can conclude that w is a function of : • Task list L • Partial order < • Time function • Number of processors n

  35. Description of the System (14) • It seems that we can improve w by: • Change the task list L • Decrease the function • Relax the partial-order < • Change the number of processors from n to n'

  36. Description of the System (15) • However, there are counter-examples show that is not always the case!! • The bound is:

  37. Description of the System (16) • Back to our greedy approach • We know that no matter how bad our design is, there is still a bound that governs the maximum time needed. • It can be proved that the bound for such a system is:

  38. Load Balancing using Mobile Agent Approach (1) • Currently, load balancing decision is centralized. • There is a switch which gathers loadinformation of all servers. • Then, it decides which machine should be chosen to assign an incoming task. • The switch may collect loading status from all machines periodically, say every 1 second.

  39. Load Balancing using Mobile Agent Approach (2) • Our approach for load-balancing decision is a decentralized one. • The computations of load balancing decision making are not performed on the switch, but on the back-end servers.

  40. Load Balancing using Mobile Agent Approach (3) • When a customer arrives, it will encapsulate the customer's request into an mobile agent • The agent will go to find a server that has the minimum load autonomously.

  41. Load Balancing using Mobile Agent Approach (4) • Multiple-Hop Mobile Agent Approach switch server server server

  42. Load Balancing using Mobile Agent Approach (5) • Advantage • We distribute the load of the switch to the server, this can increase the efficiency of the switch in creating agents. • We can have a platform-independent load balancing scheme since the dispatched agent can run on the different machines given that a unique agent execution environment is provided.

  43. Load Balancing using Mobile Agent Approach (5) • Disadvantage • our scheme will be a failure if the number of servers is too large. • As we have to travel all server once, the load information will be out-of-date or incorrect at the time when decision is made. • If the number of servers is small and the agents are migrating fast enough, this will be a very efficient scheme.

  44. Load Balancing using Mobile Agent Approach (6) • Multi-Multi-Hop Mobile Agent Approach • Since the efficiency of the multi-hop approach is restricted by the number of servers, we are now sending multiple agents in this new scheme. • After all the agents finished calculating the sub-minimal, they will gather together to calculate global minimum load.

  45. Load Balancing using Mobile Agent Approach (7) • Advantage • By using mobile agent, we can calculate the load status with respect to the nature of the service. • For example, if the task is a memory intensive process, we have no reason to treat the CPU load as the load information. • Therefore, we can plug a suitable instruction to the mobile agent in order to calculate the load status.

  46. Load Balancing using Mobile Agent Approach (8) • Disadvantage • The mobile agent approach introduces undesirable load to servers as the agents calculate the load information before the execution by incoming tasks. • Mobile agent is typically written by script language or Java. They are much slower than currently adopted approaches.

  47. Conclusion (1) • Two kinds of agents are examined: Multi-agent system and Mobile agent. • Their advantages as well as disadvantages are discussed. • Load Balancing is an old research topic, however, many domains are adopting this issues such as clusters of computers.

  48. Conclusion (2) • The possibilities of combining mobile agent and load balancing are illustrated. • This shows that with the autonomous characteristics of agents, we can improve the current load balancing decision schemes.

  49. Future Works • Continue to investigate more about agent. • Continue to think of the possibilities of combining mobile agent and load balancing techniques.

  50. ~~ END ~~