Performance of distributed information systems

There is an increasing use of distributed computer systems to provide services in both traditional telephony as well as in the Internet. Two main technologies are Distributed Object Computing (DOC) and Web based services. One common DOC architecture investigated in this thesis is the Common Object Request Broker Architecture (CORBA), specified by the Object Management Group. CORBA applications consist of interacting software components called objects. Two other DOC architectures investigated are the Telecommunications Information Net- working Architecture (TINA) and a CORBA based Intelligent Network (IN/CORBA) system. In a DOC environment, the objects of an application are distributed on mul- tiple nodes. A middleware layer makes the distribution transparent to the application. However, the distributed nature creates a number of potential performance problems. Three problems in DOC systems are examined in this thesis: object distribution, load balancing and overload protection. An object distribution describes how objects are distributed in the network. The objective is to distribute the objects on the physical nodes in such a way that intern-node communication overhead is as small as possible. One way to solve the object distribution problem is to use linear programming. The constraints for the problem are then given by both ease of management of the system and performance concerns. Load balancing is used when there are multiple objects that can be used at a particular time. The objective of load balancing is to distribute the load e±ciently on the available nodes. This thesis investigates a number of de- centralized load balancing mechanisms, including one based on the use of intelligent agents. Finally, overload protection mechanisms for DOC systems are investigated. While overload protection is well-researched for telecom networks, only little work has been performed previously concerning DOC and overload protection. Also, this thesis examines the use of overload protection in e-commerce web servers. Two schemes are compared, one which handles admission to the e-commerce site on request basis, and another which handles admission on session basis. The session based mechanism is shown to be better in terms of user-experienced performance

Experimental setup for investigating the efficient load balancing algorithms on virtual cloud

Cloud computing has emerged as the primary choice for developers in developing applications that require high-performance computing. Virtualization technology has helped in the distribution of resources to multiple users. Increased use of cloud infrastructure has led to the challenge of developing a load balancing mechanism to provide optimized use of resources and better performance. Round robin and least connections load balancing algorithms have been developed to allocate user requests across a cluster of servers in the cloud in a time-bound manner. In this paper, we have applied the round robin and least connections approach of load balancing to HAProxy, virtual machine clusters and web servers. The experimental results are visualized and summarized using Apache Jmeter and a further comparative study of round robin and least connections is also depicted. Experimental setup and results show that the round robin algorithm performs better as compared to the least connections algorithm in all measuring parameters of load balancer in this paper

Simulation of a distributed CORBA-based SCP

This paper examines load balancing issues relating to a distributed CORBA-based Service Control Point. Two types of load balancing strategies are explored through simulation studies: (i) a novel ant-based load balancing algorithm, which has been devised specically for this type of system. This algorithm is compared to more traditional algorithms, (ii) a method for optimal distribution of the computational objects composing the service programs. This is based on mathematically minimising the expected communication ows between network nodes and message-level processing costs. The simulation model has been based on the recently adopted OMG IN/CORBA Interworking specication and the TINA Service Session computational object model

QoS routing in ad-hoc networks using GA and multi-objective optimization

Much work has been done on routing in Ad-hoc networks, but the proposed routing solutions only deal with the best effort data traffic. Connections with Quality of Service (QoS) requirements, such as voice channels with delay and bandwidth constraints, are not supported. The QoS routing has been receiving increasingly intensive attention, but searching for the shortest path with many metrics is an NP-complete problem. For this reason, approximated solutions and heuristic algorithms should be developed for multi-path constraints QoS routing. Also, the routing methods should be adaptive, flexible, and intelligent. In this paper, we use Genetic Algorithms (GAs) and multi-objective optimization for QoS routing in Ad-hoc Networks. In order to reduce the search space of GA, we implemented a search space reduction algorithm, which reduces the search space for GAMAN (GA-based routing algorithm for Mobile Ad-hoc Networks) to find a new route. We evaluate the performance of GAMAN by computer simulations and show that GAMAN has better behaviour than GLBR (Genetic Load Balancing Routing).Peer ReviewedPostprint (published version

Study of Routing Protocols in Telecommunication Networks

In this paper we have discussed the problem of routing in telecommunication networks and the salient characteristics of some of the most popular routing schemes. In particular, we have discussed the characteristics of adaptive and multipath routing solutions versus static and single-path strategies

QuLa: queue and latency-aware service selection and routing in service-centric networking

Due to an explosive growth in services running in different datacenters, there is need for service selection and routing to deliver user requests to the best service instance. In current solutions, it is generally the client that must first select a datacenter to forward the request to before an internal load-balancer of the selected datacenter can select the optimal instance. An optimal selection requires knowledge of both network and server characteristics, making clients less suitable to make this decision. Information-Centric Networking (ICN) research solved a similar selection problem for static data retrieval by integrating content delivery as a native network feature. We address the selection problem for services by extending the ICN-principles for services. In this paper we present Queue and Latency, a network-driven service selection algorithm which maps user demand to service instances, taking into account both network and server metrics. To reduce the size of service router forwarding tables, we present a statistical method to approximate an optimal load distribution with minimized router state required. Simulation results show that our statistical routing approach approximates the average system response time of source-based routing with minimized state in forwarding tables