On efficient data integrity and data origin authentication for wireless sensor networks utilising block cipher design techniques

Analysis of the generic attacks and countermeasures for block cipher based message authentication code algorithms (MAC) in sensor applications is undertaken; the conclusions are used in the design of two new MAC constructs Quicker Block Chaining MAC1 (QBC-MAC1) and Quicker Block Chaining MAC2 (QBC-MAC2). Using software simulation we show that our new constructs point to improvements in usage of CPU instruction clock cycle and energy requirement when benchmarked against the de facto Cipher Block Chaining MAC (CBC-MAC) based construct used in the TinySec security protocol for wireless sensor networks.

Emergence: a paradigm for robust and scalable distributed applications

Natural distributed systems are adaptive, scalable and fault-tolerant. Emergence science describes how higher-level self-regulatory behaviour arises in natural systems from many participants following simple rulesets. Emergence advocates simple communication models, autonomy and independence, enhancing robustness and self-stabilization. High-quality distributed applications such as autonomic systems must satisfy the appropriate nonfunctional requirements which include scalability, efficiency, robustness, low-latency and stability. However the traditional design of distributed applications, especially in terms of the communication strategies employed, can introduce compromises between these characteristics. This paper discusses ways in which emergence science can be applied to distributed computing, avoiding some of the compromises associated with traditionally-designed applications. To demonstrate the effectiveness of this paradigm, an emergent election algorithm is described and its performance evaluated. The design incorporates nondeterministic behaviour. The resulting algorithm has very low communication complexity, and is simultaneously very stable, scalable and robust.

Approximation Algorithms for a Symmetric Quadratic Knapsack Problem and its Scheduling Applications

We consider a knapsack problem to minimize a symmetric quadratic function. We demonstrate that this symmetric quadratic knapsack problem is relevant to two problems of single machine scheduling: the problem of minimizing the weighted sum of the completion times with a single machine non-availability interval under the non-resumable scenario; and the problem of minimizing the total weighted earliness and tardiness with respect to a common small due date. We develop a polynomial-time approximation algorithm that delivers a constant worst-case performance ratio for a special form of the symmetric quadratic knapsack problem. We adapt that algorithm to our scheduling problems and achieve a better performance. For the problems under consideration no fixed-ratio approximation algorithms have been previously known.

Model-based pilot and data power adaptation in psam with periodic delayed feedback

We consider the optimum design of pilot-symbol-assisted modulation (PSAM) schemes with feedback. The received signal is periodically fed back to the transmitter through a noiseless delayed link and the time-varying channel is modeled as a Gauss-Markov process. We optimize a lower bound on the channel capacity which incorporates the PSAM parameters and Kalman-based channel estimation and prediction. The parameters available for the capacity optimization are the data power adaptation strategy, pilot spacing and pilot power ratio, subject to an average power constraint. Compared to the optimized open-loop PSAM (i.e., the case where no feedback is provided from the receiver), our results show that even in the presence of feedback delay, the optimized power adaptation provides higher information rates at low signal-to-noise ratios (SNR) in medium-rate fading channels. However, in fast fading channels, even the presence of modest feedback delay dissipates the advantages of power adaptation.

Models and tools for an integrated European environmental management and decision support system, (IEEMDSS)

This work proceeds from the assumption that a European environmental information and communication system (EEICS) is already established. In the context of primary users (land-use planners, conservationists, and environmental researchers) we ask what use may be made of the EEICS for building models and tools which is of use in building decision support systems for the land-use planner. The complex task facing the next generation of environmental and forest modellers is described, and a range of relevant modelling approaches are reviewed. These include visualization and GIS; statistical tabulation and database SQL, MDA and OLAP methods. The major problem of noncomparability of the definitions and measures of forest area and timber volume is introduced and the possibility of a model-based solution is considered. The possibility of using an ambitious and challenging biogeochemical modelling approach to understanding and managing European forests sustainably is discussed. It is emphasised that all modern methodological disciplines must be brought to bear, and a heuristic hybrid modelling approach should be used so as to ensure that the benefits of practical empirical modelling approaches are utilised in addition to the scientifically well-founded and holistic ecosystem and environmental modelling. The data and information system required is likely to end up as a grid-based-framework because of the heavy use of computationally intensive model-based facilities.

A design pattern approach to bitemporal data modeling

The importance of patterns in constructing complex systems has long been recognised in other disciplines. In software engineering, for example, well-crafted object-oriented architectures contain several design patterns. Focusing on mechanisms of constructing software during system development can yield an architecture that is simpler, clearer and more understandable than if design patterns were ignored or not properly applied. In this paper, we propose a model that uses object-oriented design patterns to develop a core bitemporal conceptual model. We define three core design patterns that form a core bitemporal conceptual model of a typical bitemporal object. Our framework is known as the Bitemporal Object, State and Event Modelling Approach (BOSEMA) and the resulting core model is known as a Bitemporal Object, State and Event (BOSE) model. Using this approach, we demonstrate that we can enrich data modelling by using well known design patterns which can help designers to build complex models of bitemporal databases.

X-ray crystallographic structures of neuroprotective pyrimidine derivatives: (I) the mesylate salt of BW1003C87 and (II) sipatrigine base

Drugs based on 5-phenyl-2,4 diamino pyrimidine and 6-phenyl-1,2,4 triazine derivatives are well known for their effects on the central nervous system. The study presented here provides detailed crystal structures of two pyrimidine derivatives which have neuroprotective properties in models of both grey and white matter ischemia. Recently published studies suggest that the compounds lamotrigine (a triazine derivative), and the two pyrimidines BW1003C87 (I) and sipatrigine (II) mediate their primary in vivo mode of action by inhibiting voltage-gated Na+ channels. The X-ray crystal structures will contribute valuable data for applications involving binding and modelling studies of the biological actions of these drugs.