zCap: a zero configuration adaptive paging and mobility management mechanism

Today, cellular networks rely on fixed collections of cells (tracking areas) for user equipment localisation. Locating users within these areas involves broadcast search (paging), which consumes radio bandwidth but reduces the user equipment signalling required for mobility management. Tracking areas are today manually configured, hard to adapt to local mobility and influence the load on several key resources in the network. We propose a decentralised and self-adaptive approach to mobility management based on a probabilistic model of local mobility. By estimating the parameters of this model from observations of user mobility collected online, we obtain a dynamic model from which we construct local neighbourhoods of cells where we are most likely to locate user equipment. We propose to replace the static tracking areas of current systems with neighbourhoods local to each cell. The model is also used to derive a multi-phase paging scheme, where the division of neighbourhood cells into consecutive phases balances response times and paging cost. The complete mechanism requires no manual tracking area configuration and performs localisation efficiently in terms of signalling and response times. Detailed simulations show that significant potential gains in localisation effi- ciency are possible while eliminating manual configuration of mobility management parameters. Variants of the proposal can be implemented within current (LTE) standards

Quarantine region scheme to mitigate spam attacks in wireless sensor networks

The Quarantine Region Scheme (QRS) is introduced to defend against spam attacks in wireless sensor networks where malicious antinodes frequently generate dummy spam messages to be relayed toward the sink. The aim of the attacker is the exhaustion of the sensor node batteries and the extra delay caused by processing the spam messages. Network-wide message authentication may solve this problem with a cost of cryptographic operations to be performed over all messages. QRS is designed to reduce this cost by applying authentication only whenever and wherever necessary. In QRS, the nodes that detect a nearby spam attack assume themselves to be in a quarantine region. This detection is performed by intermittent authentication checks. Once quarantined, a node continuously applies authentication measures until the spam attack ceases. In the QRS scheme, there is a tradeoff between the resilience against spam attacks and the number of authentications. Our experiments show that, in the worst-case scenario that we considered, a not quarantined node catches 80 percent of the spam messages by authenticating only 50 percent of all messages that it processe

Summary of Articles

CARAM Experiments. This file contains the simulation data (see Section Experimental results) including the risk values for several classes of CSCs for all the analyzed CSPs from STAR. (XLSX 331 kb

QoS Challenges and Opportunities in Wireless Sensor/Actuator Networks

A wireless sensor/actuator network (WSAN) is a group of sensors and actuators that are geographically distributed and interconnected by wireless networks. Sensors gather information about the state of physical world. Actuators react to this information by performing appropriate actions. WSANs thus enable cyber systems to monitor and manipulate the behavior of the physical world. WSANs are growing at a tremendous pace, just like the exploding evolution of Internet. Supporting quality of service (QoS) will be of critical importance for pervasive WSANs that serve as the network infrastructure of diverse applications. To spark new research and development interests in this field, this paper examines and discusses the requirements, critical challenges, and open research issues on QoS management in WSANs. A brief overview of recent progress is given.Comment: 12 pages, 1 figure; revie

A Brokering Framework for Assessing Legal Risks in Big Data and the Cloud

“Cloud computing” and “Big Data” are amongst the most hyped-up terms and buzzwords of the moment. After decades in which individuals and companies used to host their data and applications using their own IT infrastructure, the world has seen the stunning transformation of the Internet. Major shifts occurred when these infrastructures began to be outsourced to public Cloud providers to match commercial expectations. Storing, sharing and transferring data and databases over the Internet is convenient, yet legal risks cannot be eliminated. Legal risk is a fast-growing area of research and covers various aspects of law. Current studies and research on Cloud computing legal risk assessment have been, however, limited in scope and focused mainly on security and privacy aspects. There is little systematic research on the risks, threats and impact of the legal issues inherent to database rights and “ownership” rights of data. Database rights seem to be outdated and there is a significant gap in the scientific literature when it comes to the understanding of how to apply its provisions in the Big Data era. This means that we need a whole new framework for understanding, protecting and sharing data in the Cloud. The scheme we propose in this chapter is based on a risk assessment-brokering framework that works side by side with Service Level Agreements (SLAs). This proposed framework will provide better control for Cloud users and will go a long way to increase confidence and reinforce trust in Cloud computing transactions

Cyber risk assessment in cloud provider environments: Current models and future needs

Traditional frameworks for risk assessment do not work well for cloud computing. While recent work has often focussed on the risks faced by firms adopting or selecting cloud services, there has been little research on how cloud providers might assess their own services. In this paper, we use an in-depth review of the extant literature to highlight the weaknesses of traditional risk assessment frameworks for this task. Using examples, we then describe a new risk assessment model (CSCCRA) and compare this against three established approaches. For each approach, we consider its goals, the risk assessment process, decisions, the scope of the assessment and the way in which risk is conceptualised. This evaluation points to the need for dynamic models specifically designed to evaluate cloud risk. Our suggestions for future research are aimed at improving the identification, assessment, and mitigation of inter-dependent cloud risks inherent in a defined supply chain

Defense and Security Applications of Modeling and Simulation - Grand Challenges and Current Efforts

Proceedings of the 2012 Winter Simulation Conference C. Laroque, J. Himmelspach, R. Pasupathy, O. Rose, and A.M. Uhrmacher, edsThis paper presents the positions of seven international experts regarding current and future grand challenges for modeling and simulation (M&S) supporting the defense and security domain. Topics addressed include new interoperability issues, real-time analysis challenges, evolving military and training exercises, the future role and importance of Operations Research and M&S, modeling human teams and cultural behavior challenges, how to support successful co-evolving of research and academic programs, and the implications of enterprise postures and operational concepts of future M&S. In summary, all contributions focus on a particular facet that in summary help to understand the conceptual, technical, and organizational challenges we are currently facing