Shachi Sharma

Programmable presence virtualization for next-generation context-based applications

Presence, broadly defined as an event publish-notification infrastructure for converged applications, has emerged as a key mechanism for collecting and disseminating context attributes for next-generation services in both enterprise and provider domains. Current presence-based solutions and products lack in the ability to a) support flexible user-defined queries over dynamic presence data and b) derive composite presence from multiple provider domains. Accordingly, current uses of context are limited to individual domains/organizations and do not provide a programmable mechanism for rapid creation of context-aware services. This paper describes a presence virtualization architecture, where a Virtualized Presence Server receives customizable queries from multiple presence clients, retrieves the necessary data from the base presence servers, applies the required virtualization logic and notifies the presence clients. To support both query expressiveness and computational efficiency, virtualization queries are structured to separately identify both the XSLT-based transformation primitives and the presence sources over which the transformation occurs. For improved scalability, the proposed architecture offloads the XSLT-related processing to a high-performance XML processing engine. We describe our current implementation and present performance results that attest to the promise of this virtualization approach.

Queue length distribution of network packet traffic: Tsallis entropy maximization with fractional moments

A framework based on maximization of Tsallis entropy constrained by fractional moments is proposed to model queue length distribution of number of packets in network traffic exhibiting long-range behavior. For appropriate range of the Tsallis entropy parameter q, it is found that the first moment of number of packets may not exist Based on Euler summation formula, explicit expressions for mean queue length and buffer overflow probability exhibiting power law behavior are obtained. It is shown that in the limiting case as q tends to 1, one recovers the asymptotic results for buffer overflow probability depicting Weibull-like tail.

Power Law and Tsallis Entropy: Network Traffic and Applications

Summary. A theoretical framework based on non-extensive Tsallis entropy is proposed to study the implication of long-range dependence in traffic process on network performance. Highlighting the salient features of Tsallis entropy, the axiomatic foundations of parametric entropies are also discussed. Possible application of nonextensive thermodynamics to study the macroscopic behavior of broadband network is outlined.

q-Exponential product-form solution of packet distribution in queueing networks: maximization of Tsallis entropy

A maximum Tsallis entropy solution is presented to examine the effect of long-range dependence (LRD) of packet traffic on network of queues. An important finding is that usual product form solution of queueing networks does not hold. However, it is possible to preserve the product like structure in terms of q-product of q-exponential functions. A special case is considered when normalized q-expectation values of first moment and queue utilization at each node are available as the constraint. The joint state probability distribution is shown to depict asymptotically power law behavior

Bimodal packet distribution in loss systems using maximum Tsallis entropy principle

A theoretical model of loss system is proposed and analysed within the framework of maximum Tsallis entropy principle. The study provides an explicit expression for state probability distribution of packets in presence of long-range dependent traffic. The unimodal state probability distribution corresponding to well-known Erlangs loss formula is recovered for Tsallis entropy parameter q = 1. As the parameter q is lowered from unity, it is shown that the state probability distribution makes a transition from unimodal to bimodal. The emergence of bimodality can be regarded as a consequence of long-range dependence. The implication of the model in the design of loss systems is discussed.

Presence virtualization middleware for next-generation converged applications

This paper describes the initial design of a scalable and client-programmable presence virtualization architecture.

Power law characteristics and loss probability: finite buffer queueing systems

Analytical framework based on maximum Tsallis entropy is proposed for studying finite buffer queueing system when information about fractional moment of queue size and utilization is available. The framework enables us to obtain closed form expressions for queue length distribution and loss probability for generalized M/M/1/N system when input to the system possesses power law characteristics. It is shown that queue length distribution depicts power law as the number of units in the system becomes large. A new result for asymptotic loss probability exhibiting power law behavior is derived.

Pressentials : a flexible middleware for presence-enabled applications

Presence, broadly defined as an event publish-notification infrastructure based on unified communication protocols such as SIP or XMPP, is a key enabler for rich, contextual communication and collaboration. This paper presents the design, implementation and experimental evaluation of Pressentials - a large-scale presence federation and virtualization middleware for enabling context-aware applications. This middleware provides a programmatic interface for aggregating presence from various sources and for composing base presence information into abstract, functionally richer entities for enabling applications. An underlying design consideration is to leverage capabilities of protocols that are being widely deployed today. We present scaling algorithms used within the platform to re-use data and computation commonalities across multiple applications. To highlight the flexibility of the proposed framework, we discuss use-case scenarios (across multiple domains) built using this platform.

HiCHO: Attributes Based Classification of Ubiquitous Devices

An online and incremental clustering method to classify heterogeneous devices in dynamic ubiquitous computing environment is presented. The proposed classification technique, HiCHO, is based on attributes characterizing devices. These can be logical and physical attributes. Such classification allows to derive class level similarity or dissimilarity between devices and further use it to extract semantic information about relationship among devices. The HiCHO technique is protocol neutral and can be integrated with any device discovery protocol. Detailed simulation analysis and real-world data validates the efficacy of the HiCHO technique and its algorithms.

Presence based network topology tracing system for VoIP networks

Tracing topology of services in real-time is a challenging problem in VoIP networks. The primary reason is that the VoIP networks operate with diverse interconnecting protocols, technologies, and multitude of access technologies. In addition, alliances, changing rules and regulations, mergers, new technologies and services impact architecture of VoIP networks consistently. All of these together results in heterogeneous, complex and dynamic VoIP networks where the network topology changes very frequently. Secondly, in case of voice, each call can follow a different path over the core IP infrastructure in the network. Even the signaling and media path of the same voice call can follow different paths to destination (callees device). Stitching and providing integrated end to end cross layer view of the path in real-time of an ongoing service flow e.g. voice call under such unpredictable network conditions is difficult.