Manish Parashar

Autonomic computing: an overview

The increasing scale complexity, heterogeneity and dynamism of networks, systems and applications have made our computational and information infrastructure brittle, unmanageable and insecure. This has necessitated the investigation of an alternate paradigm for system and application design, which is based on strategies used by biological systems to deal with similar challenges – a vision that has been referred to as autonomic computing. The overarching goal of autonomic computing is to realize computer and software systems and applications that can manage themselves in accordance with high-level guidance from humans. Meeting the grand challenges of autonomic computing requires scientific and technological advances in a wide variety of fields, as well as new software and system architectures that support the effective integration of the constituent technologies. This paper presents an introduction to autonomic computing, its challenges, and opportunities.

A Peer-to-Peer Approach to Web Service Discovery

Web Services are emerging as a dominant paradigm for constructing and composing distributed business applications and enabling enterprise-wide interoperability. A critical factor to the overall utility of Web Services is a scalable, flexible and robust discovery mechanism. This paper presents a Peer-to-Peer (P2P) indexing system and associated P2P storage that supports large-scale, decentralized, real-time search capabilities. The presented system supports complex queries containing partial keywords and wildcards. Furthermore, it guarantees that all existing data elements matching a query will be found with bounded costs in terms of number of messages and number of nodes involved. The key innovation is a dimension reducing indexing scheme that effectively maps the multidimensional information space to physical peers. The design and an experimental evaluation of the system are presented.

Latency Performance of SOAP Implementations

This paper presents an experimental evaluation of the latency performance of several implementations of Simple Object Access Protocol (SOAP) operating over HTTP, and compares these results with the performance Of JavaRMI, CORBA, HTTP, and with the TCP setup time. SOAP is an XML based protocol that supports RPC and message semantics. While SOAP has been designed as an interoperable business-to-business protocol usable over the Internet, we believe that applications will also use SOAP for interactive web applications running within an intranet. The objective of this paper is to identify the sources of inefficiency in the current implementations of SOAP and discuss changes that can improve their performance. SOAP implementations studied include Microsoft SOAP Toolkit, the SOAP: Lite Perl module, and Apache SOAP.

Flexible information discovery in decentralized distributed systems

The ability to efficiently discover information using partial knowledge (for example keywords, attributes or ranges) is important in large, decentralized, resource sharing distributed environments such as computational grids and peer-to-peer (P2P) storage and retrieval systems. This paper presents a P2P information discovery system that supports flexible queries using partial keywords and wildcards, and range queries. It guarantees that all existing data elements that match a query are found with bounded costs in terms of number of messages and number of peers involved. The key innovation is a dimension reducing indexing scheme that effectively maps the multidimensional information space to physical peers. The design, implementation and experimental evaluation of the system are presented.

Towards autonomic workload provisioning for enterprise Grids and clouds

This paper explores autonomic approaches for optimizing provisioning for heterogeneous workloads on enterprise Grids and clouds. Specifically, this paper presents a decentralized, robust online clustering approach that addresses the distributed nature of these environments, and can be used to detect patterns and trends, and use this information to optimize provisioning of virtual (VM) resources. It then presents a model-based approach for estimating application service time using long-term application performance monitoring, to provide feedback about the appropriateness of requested resources as well as the systems ability to meet QoS constraints and SLAs. Specifically for high-performance computing workloads, the use of a quadratic response surface model (QRSM) is justified with respect to traditional models, demonstrating the need for application-specific modeling. The proposed approaches are evaluated using a real computing center workload trace and the results demonstrate both their effectiveness and cost-efficiency.

AutoMate: enabling autonomic applications on the grid

The increasing complexity, heterogeneity and dynamism of networks, systems, services applications have made our computational/information infrastructure brittle, unmanageable and insecure. This has necessitated the investigation of a new paradigm for design, development and deployment based on strategies used by biological systems to deal with complexity, heterogeneity, and uncertainty, i.e. autonomic computing. This paper introduces the AutoMate project and describes its key components. The overall objective of AutoMate is to investigate key technologies to enable the development of autonomic grid applications that are context aware and are capable of self-configuring, self-composing, self-optimizing and self-adapting. Specifically, it will investigate the definition of autonomic components, the development of autonomic applications as dynamic composition of autonomic components, and the design of key enhancements to existing grid middleware and runtime services to support these applications.

Enabling flexible queries with guarantees in P2P systems

The Squid peer-to-peer information discovery system supports flexible queries using partial keywords, wildcards, and ranges. It is built on a structured overlay and uses data lookup protocols to guarantee that all existing data elements that match a query are found efficiently. Its main innovation is a dimension-reducing indexing scheme that effectively maps multidimensional information space to physical peers.

A component-based programming model for autonomic applications

The emergence of pervasive wide-area distributed computing environments, such as pervasive information systems and computational grids, has enabled new generations of applications that are based on seamless access, aggregation and interaction. However, the inherent complexity, heterogeneity and dynamism of these systems require a change in how the applications are developed and managed. In this paper we present a component-based programming framework to support the development of autonomic self-managed applications. The framework enables the development of autonomic components and the formulation of autonomic applications as the dynamic composition and management of autonomic components. The operation of the proposed framework is illustrated using a forest fire application.

A concise introduction to autonomic computing

1. IntroductionThe advances in computing and communication tech-nologies and software have resulted in an explosive growthin computing systems and applications that impact allaspects of our life. However, as the scale and complexity ofthese systems and applications grow, their development,configuration and management challenges are beginning tobreak current paradigms, overwhelm the capabilities ofexisting tools and methodologies, and rapidly render thesystems and applications brittle, unmanageable andinsecure.This has led researchers to consider alternativeapproaches based on strategies used by biological systemsto successfully deal with similar challenges of complexity,dynamism, heterogeneity and uncertainty. Autonomiccomputing is emerging as a significant new strategic andholistic approach to the design of complex distributedcomputer systems. It is inspired by the functioning of thehuman nervous system and is aimed at designing andbuilding systems that are self-managing. Morespecifically, an autonomic system is a self-managing,autonomous and ubiquitous computing environment thatcompletely hides its complexity, thus providing the userwith an interface that exactly meets her/his needs. Thesystem will always decide on its own, using high-levelguidance from humans, what needs to be done to keep itstable. It will constantly check and optimize its status,and automatically adapt itself to changing conditions.Self-management is achieved through key aspects such asself-governing, self-adaptation, self-organization, self-optimization, self-configuration, self-diagnosis of faults,self-protection, self-healing, self-recovery, and autonomy.Achieving these goals come down to bringing pre-emptiveand proactive approaches to all areas of a computingsystem. Meeting these challenges of autonomic computingrequires scientific and technological advances in a widevariety of fields, and new architectures that supporteffective integration of the constituent technologies.2. ConceptsBiological systems have inspired systems design in manyways—Artificial Intelligence, Artificial Neural Networks,Genetic Algorithms, Genetic Programming, and HolonicSystems to name a few. The most recent is the inspiration tocreate self-managing systems.2.1. Autonomic nervous systemThe human body’s Autonomic Nervous System (ANS) isthe part of the nervous system that controls the vegetativefunctions of the body such as circulation of the blood,intestinal activity and secretion, and the production ofchemical ‘messengers’, i.e. hormones, that circulate in

Cloud federation in a layered service model

We show how a layered Cloud service model of software (SaaS), platform (PaaS), and infrastructure (IaaS) leverages multiple independent Clouds by creating a federation among the providers. The layered architecture leads naturally to a design in which inter-Cloud federation takes place at each service layer, mediated by a broker specific to the concerns of the parties at that layer. Federation increases consumer value for and facilitates providing IT services as a commodity. This business model for the Cloud is consistent with broker mediated supply and service delivery chains in other commodity sectors such as finance and manufacturing. Concreteness is added to the federated Cloud model by considering how it works in delivering the Weather Research and Forecasting service (WRF) as SaaS using PaaS and IaaS support. WRF is used to illustrate the concepts of delegation and federation, the translation of service requirements between service layers, and inter-Cloud broker functions needed to achieve federation.