Mobile browsing habits are characteristically different from browsing on traditional devices. Mobile users often look for information snippets instead of complete web pages. Also, mobile devices are often constrained in terms of resource availability, such as battery, data plan limits and network bandwidth. Under such constraints, partial-loading of a web page, by loading the most relevant content snippets early, can satisfy the user and consume less resources. Mobile content adaptation middleware has traditionally focused on user factors, such as user feedbacks and user context. We believe that the content creator, with complete knowledge of the importance of each item in the web page, is well-suited to guide the adaptation process. Combining user choice, and ratings assigned by the content creator to different web page elements (items), enables delivering the most relevant items in an ordered manner in response to a page request. We present ScoDA, a cooperative content adaptation middleware framework, under resource constraints. We evaluate the effectiveness of page loading using ScoDA, on simulated complex web pages as well as real web pages.

WiFi-based indoor localization solutions are actively in commercial use today. WiFi radio maps are typically created in an offline process, and location estimation is performed in realtime (online) using the maps. Both the radio map and the signal strengths provided as input during the online phase are affected by several dynamic factors resident in the environment. We call these “causality factors”. Hence, the online location accuracy is far from the quality achieved in laboratory tests with training data, since the causality factors have varied in between. This impacts the quality expected by heterogeneous applications in real deployments. To address this issue, we investigate a novel online dynamic calibration methodology called KARMA. KARMA utilizes a one-time fingerprint of the space and systematically applies a set of causality calibration functions in real-time to compensate for the change in the factors, at test time. As a result, location providers can now significantly reduce the costly re-learning of the models for different factors, and improve real-time location prediction accuracy. Experimental studies demonstrate that KARMA's strategy, while keeping the fingerprinting task contained, can improve localization quality by a factor of 2x, compared to a typical one-state fingerprinting approach employed in many commercial deployments today. It also compares very favorably with an exhaustive all-state fingerprinting approach.

There is tremendous interest in exploiting smartphones as a “community of sensors”. It is envisioned that this community-driven smartphone sensor network has unprecedented potential to sense heterogeneous phenomena ranging from sound pollution to urban social dynamics. However, designing smartphone-resident middleware for opportunistic and objectiveoriented sensing of these phenomena is an open challenge. In this paper, we propose USense, a novel utility-driven smartphone middleware for executing community-driven sensing tasks. USense is different from other mobile phone sensing frameworks in the following ways: it is (i) Application aware, i.e., it adapts its operation based on demands of the application (ii) User aware, i.e., it incorporates preferences, policies as well as behavioral history of the user carrying the phone, and (iii) Situation aware, i.e. it considers resource dynamics on the phone at any given point. We argue that these three aspects are essentially decoupled in nature and combining them effectively is the key towards designing a re-usable and scalable middleware. Based on an extensible model for `Sensing Moments', USense first allows application developers to easily create sensing tasks. Secondly, we propose a unified device middleware to simultaneously execute the sensing tasks at the right moments across multiple applications. We have implemented USense on the Android platform, and demonstrate its effectiveness through real-life data traces.

With rapid advancement in the capabilities of mobile phones, there has been a tremendous increase in the development and use of mobile applications in recent times. Surprisingly, Telecom operators have not been prominent players in the success of mobile applications and the corresponding mobile Application Stores. We argue that, to offset this going forward, Telecom operators can utilize some of their core strengths to create differentiated Application Stores that will help them compete effectively with their competitors. More specifically, Telecom operators have access to unique data which is not available elsewhere, this can be used to give new insights on their customers and offer them relevant mobile applications. In this paper, we present techniques on how applications can be promoted effectively from a Telecom Application Store utilizing the users' location, their Telecom profiles as well as their social relationships derived from their calling patterns. Moreover, we provide a bidding platform that gives control to developers for highlighting their application by placing bids on multiple Telecom parameters.

Recent technological advances in mobile-based access to social networking platforms and facilities to update information in real{time (e.g. in Facebook) have allowed an individual's online presence to be as ephemeral and dynamic in nature, as her very thoughts and interests. In this context, micro-blogging has been widely adopted by users as an effective means to capture and disseminate their thoughts and actions to a larger audience on a daily basis. Interestingly, daily chatters of a user obtained from her micro-blogs offer a unique information source to analyze and interpret her context in real-time - i.e. interests, intentions,and activities. In this paper, we gather data from the public timeline of Twitter spanning across ten worldwide cities over a period of four weeks. We use this dataset to (a) explore how users express interests in real-time through micro-blogs, and (b) understand how text mining techniques can be applied to interpret real-time context of a user based on her tweets. Initial findings reported herein suggest that social media sites like Twitter constitute a promising source for extracting user context that can be exploited by novel social networking applications.

With the growing popularity of social networking, traditional Internet Service Providers (ISPs) and telecom operators have both started exploring new opportunities to boost their revenue streams. The efforts have facilitated consumers to stay connected to their favorite social networks,be it from an ISP portal or a mobile device. The use of Web 2.0 technologies and converged communication tools has further led to a rise in both user-generated content as well as contextual information (i.e. rich presence) about users - including their current location, availability, interests and moods. In this evolving landscape, social networking players need to innovate for value-centric usage models that increase customer stickiness,along with business models to monetize the social media. To this end, we present R-U-In? - an activity-oriented social networking system for users to collaborate and participate in activities of mutual interest. Activities can be initiated and scheduled on-demand and be as ephemeral as the user interests themselves. R-U-In? leverages contextual modeling and reasoning techniques to enable ldquosocial searchrdquo based on real-time user interests and finds potential matches for the proposed activity. Further, it exploits next-generation presence and communication technologies to manage the entire activity lifecycle in real-time. Initial survey results, based on a prototype implementation of R-U-In?, attest to the promise of realtime activity-oriented social networking - both in terms of an effective collaboration tool for value-oriented social networking users and an enhanced end-user experience.

Data migration has become a priority in many industries, spawned by a variety of business needs. Most of the existing tools for Extract, Transform and Load (ETL) process of data migration are piece-meal and do not present a complete solution. Moreover, while research has focused on the problem of Schema Mapping, a key step in the ETL process, most of the current algorithms do not perform well on real-world data. Researchers have suggested the use of Domain Knowledge to enhance schema mapping. In this paper, we use domain knowledge in an innovative manner to improve schema mapping in an 'actual' industrial setting. Further, we take a comprehensive view of the data migration problem and present an end-to-end system for the ETL process, utilizing existing tools for each step and building connectors, wherever required. We focus on Data Migration for Telecom Billing and utilize domain knowledge captured in an ontology, a thesaurus and a set of rules to improve schema mapping. Experiments conducted on a real-life data demonstrate the effectiveness of our system and validate the utility of domain knowledge in data migration projects.

This paper presents R-U-In? - a social networking application that leverages Web 2.0 and IMS-based Converged Networks technologies to create a rich next-generation service. R-U-In? allows a user to search (in real-time) and solicit participation of like-minded partners for an activity of mutual interest (e.g. a rock concert, a soccer game, or a movie). It is an example of a situational mashup application that exploits content and capabilities of a Telecom operator, blended with Web 2.0 technologies, to provide an enhanced, value-added service experience.

With Telecom market reaching saturation in many geographies and revenues from voice calls decreasing, Telecom operators are trying to identify new sources of revenue. For this purpose, these operators can take advantage of their core functionalities like Location, Call Control, etc. by exposing them as services to be composed by developers with third party offerings available over the Web. To hide the complexity of underlying Telecom protocols from application developers, the operators are steadily adopting Service Oriented Architecture (SOA) and reference standards like Parlay-X and IMS. However, a number of challenges still remain in rapid utilization of Telecom functionalities for creating new applications - existence of multiple protocols, different classes of developers, and the need to coordinate and manage usage of these functionalities. In this paper, we present SewNet, a framework for creating applications exploiting Telecom functionality exposed over a (converged) IP network. More specifically, SewNet a) provides an abstraction model for encapsulating invocation, coordination and enrichment of the Telecom functionalities, b) renders a service creation environment on top of this model, and c) caters to various different categories of developers. With the help of two use-case scenarios, we demonstrate how SewNet can create services utilizing rich Telecom functionality.

Web services provide an instantiation of the loosely coupled service–oriented architecture and facilitate the process of enterprise application integration by encapsulating information, software, and other resources. However, to exploit the true potential of web services, it is critical to develop technologies and tools for composing new services from existing ones. While numerous composition approaches have been developed in the past, very little has been done towards tooling. What is clearly lacking is an Integrated Development Environment (IDE) to ease the process of composition, thereby reducing development time and integration efforts. In this paper, we build on our previous work on service composition, and present an IDE for end–to–end composition of web services. We elaborate on the design of the IDE, describe its integration with existing technologies, and discuss its usability based on the findings of a user survey.

Workflows often operate in volatile environments in which the component services' QoS changes frequently. Optimally adapting to these changes becomes an important problem that must be addressed by the Web service composition and execution (WSCE) system being utilized. We adopt the A-WSCE framework that utilizes a three-stage approach for composing and executing Web workflows. The A-WSCE framework offers a way to adapt by defining multiple workflows and switching among them in case of component failure or changes in the QoS parameters. However, the A-WSCE framework suffers from the limitations imposed by a simple strategy of periodically checking the QoS offerings of randomly picked providers in order to decide whether the current workflow is optimal. To address these limitations, we associate the value of changed information (VOC) with each workflow and utilize the VOC to update which workflow to execute. We empirically demonstrate the improved performance of the workflows selected using the new approach in comparison to the original framework.

Web services simplify enterprise application integration by facilitating reuse of existing components for creating new services. In a dynamic environment, it is imperative to design a Web Service Composition and Execution (WSCE) system that adapts to failure of component services or changes in their QoS offerings. In this paper, we motivate a staged approach for adaptive WSCE (A-WSCE) that cleanly separates the functional and non-functional requirements of a new service, and enables different environmental changes to be absorbed at different stages of composition and execution. We use Synthy, a prototype service creation environment, to implement our solution and demonstrate its effectiveness.

Smart environments that can adapt based on the current context are extremely useful for automating even simple, mundane tasks. The key components of such an environment are sources that can extract the raw context, a synthesizer that can draw inferences by aggregating the context from different sources, and a set of policies that drive the adaptation. In this paper, we describe a context-based adaptation system to alleviate the distraction caused by one of the most ubiquitous devices of modern day-the mobile phone. Our system makes use of sources, such as RFID devices, that employ near-field communication technology to extract raw context. We describe how we adapt the roles of these devices to extract both environmental and personal context. To reduce the distraction caused by mobile phones, we have developed a policy-based mechanism to enable context-based adaptation of these devices. We have implemented a prototype of our system and conducted some usage studies. We describe the details of our implementation and present the lessons learned from the usability experiments

The demand for quickly delivering new applications is increasingly becoming a business imperative today. Application development is often done in an ad hoc manner, without standard frameworks or libraries, thus resulting in poor reuse of software assets. Web services have received much interest in industry due to their potential in facilitating seamless business-to-business or enterprise application integration. A web services composition tool can help automate the process, from creating business process functionality, to developing executable workflows, to deploying them on an execution environment. However, we find that the main approaches taken thus far to standardize and compose web services are piecemeal and insufficient. The business world has adopted a (distributed) programming approach in which web service instances are described using WSDL, composed into flows with a language like BPEL and invoked with the SOAP protocol. Academia has propounded the AI approach of formally representing web service capabilities in ontologies, and reasoning about their composition using goal-oriented inferencing techniques from planning. We present the first integrated work in composing web services end to end from specification to deployment by synergistically combining the strengths of the above approaches. We describe a prototype service creation environment along with a use-case scenario, and demonstrate how it can significantly speed up the time-to-market for new services.