Swarm Intelligence Heuristics for Component Deployment

We address the problem of efficient deployment of software services into a networked environment. Services are considered that are provided by collaborating components. The problem of obtaining efficient mappings for components to host in a network is challenged by multiple dimensions of quality of service requirements. In this paper we consider execution costs for components and communication costs for the collaborations between them. Our proposed solution to the deployment problem is a nature inspired distributed heuristic algorithm that we apply from the service provider's perspective. We present simulation results for different example scenarios and present an integer linear program to validate the results obtained by simulation of our algorithm.

[1]  Kemal Efe,et al.  Heuristic Models of Task Assignment Scheduling in Distributed Systems , 1982, Computer.

[2]  Calton Pu,et al.  Generating Adaptation Policies for Multi-tier Applications in Consolidated Server Environments , 2008, 2008 International Conference on Autonomic Computing.

[3]  Bjarne E. Helvik,et al.  Using the Cross-Entropy Method to Guide/Govern Mobile Agent's Path Finding in Networks , 2001, MATA.

[4]  Jing Xu,et al.  On the Use of Fuzzy Modeling in Virtualized Data Center Management , 2007, Fourth International Conference on Autonomic Computing (ICAC'07).

[5]  Poul E. Heegaard,et al.  Overhead reduction in a distributed path management system , 2010, Comput. Networks.

[6]  Christian Nyberg,et al.  Cross entropy based module alocation for distributed systems , 2004 .

[7]  E. Horlait.  Mobile Agents for Telecommunication Applications , 2003, Lecture Notes in Computer Science.

[8]  Frank Eliassen,et al.  Composing Components and Services Using a Planning-Based Adaptation Middleware , 2008, SC@ETAPS.

[9]  R. Rubinstein.  The Cross-Entropy Method for Combinatorial and Continuous Optimization , 1999 .

[10]  Danilo Ardagna,et al.  SLA based resource allocation policies in autonomic environments , 2007, J. Parallel Distributed Comput..

[11]  Peter Herrmann,et al.  Adaptable model-based component deployment guided by artificial ants , 2008, Autonomics.

[12]  Tales Heimfarth,et al.  Ant Based Heuristic for OS Service Distribution on Ad Hoc Networks , 2006, BICC.

[13]  Hartmut Schmeck,et al.  Biologically Inspired Cooperative Computing, IFIP 19th World Computer Congress, TC 10: 1st IFIP International Conference on Biologically Inspired Computing, August 21-24, 2006, Santiago, Chile , 2006, BICC.

[14]  Hein Meling,et al.  Foraging for Better Deployment of Replicated Service Components , 2009, DAIS.

[15]  Peter Herrmann,et al.  Cost-Efficient Deployment of Collaborating Components , 2008, DAIS.

[16]  Marco Dorigo,et al.  AntNet: Distributed Stigmergetic Control for Communications Networks , 1998, J. Artif. Intell. Res..

[17]  Ritu Sabharwal.  Grid Infrastructure Deployment using SmartFrog Technology , 2006, International conference on Networking and Services (ICNS'06).

[18]  S. Malek.  A User-Centric Framework for Improving a Distributed Software System ’ s Deployment Architecture , 2006 .

[19]  Poul E. Heegaard,et al.  The Cross Entropy Ant System for Network Path Management , 2008 .

[20]  Otto Wittner,et al.  Emergent behavior based implements for distributed network management , 2003 .