Introduction to the special section on dependable network computing

Dependable network computing is becoming a key part of our daily economic and social life. Every day, millions of users and businesses are utilizing the Internet infrastructure for real-time electronic commerce transactions, scheduling important events, and building relationships. While network traffic and the number of users are rapidly growing, the mean-time between failures (MTTF) is surprisingly short; according to recent studies, in the majority of Internet backbone paths, the MTTF is 28 days. This leads to a strong requirement for highly dependable networks, servers, and software systems. The challenge is to build interconnected systems, based on available technology, that are inexpensive, accessible, scalable, and dependable. This special section provides insights into a number of these exciting challenges

An infrastructure service recommendation system for cloud applications with real-time QoS requirement constraints

The proliferation of cloud computing has revolutionized the hosting and delivery of Internet-based application services. However, with the constant launch of new cloud services and capabilities almost every month by both big (e.g., Amazon Web Service and Microsoft Azure) and small companies (e.g., Rackspace and Ninefold), decision makers (e.g., application developers and chief information officers) are likely to be overwhelmed by choices available. The decision-making problem is further complicated due to heterogeneous service configurations and application provisioning QoS constraints. To address this hard challenge, in our previous work, we developed a semiautomated, extensible, and ontology-based approach to infrastructure service discovery and selection only based on design-time constraints (e.g., the renting cost, the data center location, the service feature, etc.). In this paper, we extend our approach to include the real-time (run-time) QoS (the end-to-end message latency and the end-to-end message throughput) in the decision-making process. The hosting of next-generation applications in the domain of online interactive gaming, large-scale sensor analytics, and real-time mobile applications on cloud services necessitates the optimization of such real-time QoS constraints for meeting service-level agreements. To this end, we present a real-time QoS-aware multicriteria decision-making technique that builds over the well-known analytic hierarchy process method. The proposed technique is applicable to selecting Infrastructure as a Service (IaaS) cloud offers, and it allows users to define multiple design-time and real-time QoS constraints or requirements. These requirements are then matched against our knowledge base to compute the possible best fit combinations of cloud services at the IaaS layer. We conducted extensive experiments to prove the feasibility of our approach

Technologies and solutions for location-based services in smart cities: past, present, and future

Location-based services (LBS) in smart cities have drastically altered the way cities operate, giving a new dimension to the life of citizens. LBS rely on location of a device, where proximity estimation remains at its core. The applications of LBS range from social networking and marketing to vehicle-toeverything communications. In many of these applications, there is an increasing need and trend to learn the physical distance between nearby devices. This paper elaborates upon the current needs of proximity estimation in LBS and compares them against the available Localization and Proximity (LP) finding technologies (LP technologies in short). These technologies are compared for their accuracies and performance based on various different parameters, including latency, energy consumption, security, complexity, and throughput. Hereafter, a classification of these technologies, based on various different smart city applications, is presented. Finally, we discuss some emerging LP technologies that enable proximity estimation in LBS and present some future research areas

Privacy Preserving Location-Based Client-Server Service Using Standard Cryptosystem

Location-Based Mobile Services (LBMS) is rapidly gaining ground and becoming increasingly popular, because of the variety of efficient and personalized services it offers. However, if users are not guaranteed their privacy and there is no assurance of genuineness of server\u27s response, the use of these services would be rendered useless and could deter its growth in mobile computing. This paper aims to provide confidentiality and integrity for communication that occurs between users and location service providers. A practical system that guarantees a user\u27s privacy and integrity of server\u27s response, using a cryptographic scheme with no trusted intermediary, is provided. This scheme also employs the use of symmetric and asymmetric encryption algorithms to ensure secure message and key transfer. In order to overcome the problem of computational complexities with these algorithms, AES-256 is used to encrypt the message and user\u27s location. Several researches have been done in this category but there is still no system that checks the integrity of server\u27s response. The proposed scheme is resistant to a range of susceptible attacks, because it provides a detailed security analysis and, when compared with related work, shows that it can actually guarantee privacy and integrity with faster average response time and higher throughput in LBMS

Advances in Data Modeling Research

In this paper, we summarize the discussions of the panel on Advances in Data Modeling Research, held at the Americas Conference on Information Systems (AMCIS) in 2005. We focus on four primary areas where data modeling research offers rich opportunities: spatio-temporal semantics, genome research, ontological analysis and empirical evaluation of existing models. We highlight past work in each area and also discuss open questions, with a view to promoting future research in the overall data modeling area

Emergency Response Information System Interoperability: Development of Chemical Incident Response Data Model

Emergency response requires an efficient information supply chain for the smooth operations of intra- and inter-organizational emergency management processes. However, the breakdown of this information supply chain due to the lack of consistent data standards presents a significant problem. In this paper, we adopt a theory- driven novel approach to develop an XML-based data model that prescribes a comprehensive set of data standards (semantics and internal structures) for emergency management to better address the challenges of information interoperability. Actual documents currently being used in mitigating chemical emergencies from a large number of incidents are used in the analysis stage. The data model development is guided by Activity Theory and is validated through a RFC-like process used in standards development. This paper applies the standards to the real case of a chemical incident scenario. Further, it complies with the national leading initiatives in emergency standards (National Information Exchange Model

Current State of Information Security Research In IS

The importance of information security in a pervasive networked environment is undeniable, yet there is a lack of research in this area. In this study we conduct a comprehensive survey of the information security articles published in leading IS journals. We then compared the research themes with those of the IBM Information Security Capability Reference Model