Load-balancing metrics for adaptive dispatching of long asynchronous network requests

• US 20070143460A1
• Filed: 12/19/2005
• Published: 06/21/2007
• Est. Priority Date: 12/19/2005
• Status: Abandoned Application

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Ben-David, Shay, Roytman, Alexey
• Application Number:
  US11/311,790
• Publication Number:
  US 20070143460A1
• Time in Patent Office: Days
• US Class Current: 709/223
• CPC Class Codes: G06F 9/505 considering the load
• CPC Class Codes: G06F 9/5083 Techniques for rebalancing the load in a distributed system
• CPC Class Codes: H04L 67/1001 for accessing one among a plurality of replicated servers
• CPC Class Codes: H04L 67/1008 based on parameters of servers, e.g. available memory or workload monitoring of computer activity G06F11/30

Abstract

Methods and systems are provided for load-balancing a data network, which is configured with a plurality of servers for servicing client requests asynchronously, and with a network dispatcher for assigning each new request to a selected server. The servers generate metrics indicative of their currently assigned workloads. The network dispatcher receives the metrics, and allocates requests according to weighted server probabilities reflecting the servers'"'"' capabilities and the metrics. Connections with the client are thereupon terminated, and reinstated after service of the request. The servers may be weighted in accordance with their respective capabilities, and the metrics adjusted by the weights.

Claims

1. A computer-implemented method for load-balancing a data network having at least one client connectable thereto and a cluster of servers for servicing said client, said servers each having a job queue and said job queue having a length, the method comprising the steps of;

establishing a connection extending from said client to said cluster of servers;

receiving a request from said client;

in said servers generating respective metrics indicative of currently assigned jobs therein;

responsively to said metrics, assigning weight values to said servers; and

allocating said request to one of said servers according to said weight values for service thereof.

2. The method according to claim 1, further comprising the step of prior to completing said service, terminating said connection.

3. The method according to claim 1, wherein said step of allocating said request comprises computing weighted server probabilities for said servers, and assigning one of said servers to service said request according to said weighted server probabilities.

4. The method according to claim 3, wherein assigning one of said servers is performed using a Monte Carlo method.

5. The method according to claim 1, further comprising the step of identifying a minimally loaded server, and allocating said request is performed by choosing said minimally loaded server.

6. The method according to claim 1, wherein said step of assigning weight values comprises the steps of:

assigning initial weight values to said servers that are indicative of respective capabilities thereof; and

adjusting said initial weight values according to said metrics.

7. The method according to claim 6, wherein said step of assigning weight values is performed periodically at predetermined intervals.

8. The method according to claim 6, wherein said step of assigning weight values is performed repeatedly after completion of a predetermined number of requests.

9. The method according to claim 6, wherein said step of assigning weight values is performed repeatedly after receiving a predetermined number of requests.

10. The method according to claim 1, wherein said metrics comprise a function of said length of said job queue.

11. The method according to claim 1, wherein said servers comprise a plurality of execution engines, and generating respective metrics comprises the steps of:

assigning respective workload weights to said execution engines that are indicative of server resources consumed by said execution engines; and

multiplying a number of tasks currently assigned to each of said execution engines by said respective workload weights.

12. A computer software product for load-balancing a data network having at least one client connectable thereto and a cluster of servers for servicing said client, the product including a computer-readable medium in which computer program instructions are stored, which instructions, when read by a computer, cause the computer to establish a connection extending from said client to said cluster of servers, to receive a request from said client, to receive from said servers respective metrics indicative of currently assigned jobs therein, responsively to said metrics, to assign weight values to said servers, and to allocate said request to one of said servers according to said weight values for service thereof.

13. The computer software product according to claim 12, wherein said instructions further cause said computer to terminate said connection prior to completing said service.

14. The computer software product according to claim 12, wherein said instructions further cause said computer to compute weighted server probabilities for said servers, and to assign one of said servers to service said request according to said weighted server probabilities.

15. The computer software product according to claim 12, wherein said instructions further cause said computer to assign initial weight values to said servers that are indicative of respective capabilities thereof, and to adjust said initial weight values according to said metrics.

16. The computer software product according to claim 15, wherein said instructions further cause said computer to assign weight values periodically at predetermined intervals.

17. The computer software product according to claim 15, wherein said instructions further cause said computer to assign weight values repeatedly after completion of a predetermined number of requests.

18. A network dispatcher for load-balancing a data network having at least one client connectable thereto and a plurality of servers for servicing said client, comprising a processor operative to receive a request from said client, to receive from said servers respective metrics indicative of currently assigned jobs therein, responsively to said metrics, to assign weight values to said servers;

and to allocate said request to one of said servers according to said weight values for service thereof.

19. The network dispatcher according to claim 18, wherein said processor is further operative to assign initial weight values to said servers that are indicative of respective capabilities thereof;

and to adjust said initial weight values according to said metrics.

20. The network dispatcher according to claim 18, wherein said processor is operative to compute weighted server probabilities for said servers, and to assign one of said servers to service said request according to said weighted server probabilities.