Theoretical and Applied Informatics

The predicted annual growth of energy consumption in ICT by 4% towards 2020, despite improvements and efficiency gains in technology, is challenging our ability to claim that ICT is providing overall gains in energy efficiency and Carbon Imprint as computers and networks are increasingly used in all sectors of activity. Thus we must find means to limit this increase and preserve quality of service (QoS) in computer systems and networks. Since the energy consumed in ICT is related to system load, ]this paper discusses the choice of system load that offers the best trade-off between energy consumption and QoS. We use both simple queueing models and measurements to develop and illustrate the results. A discussion is also provided regarding future research directions.

The problem that this paper investigates, namely, optimization of overlay computing systems, follows naturally from growing need for effective processing and consequently, fast development of various distributed systems. We consider an overlay-based computing system, i.e., a virtual computing system is deployed on the top of an existing physical network (e.g., Internet) providing connectivity between computing nodes. The main motivation behind the overlay concept is simple provision of network functionalities (e.g., diversity, flexibility, manageability) in a relatively cost-effective way as well as regardless of physical and logical structure of underlying networks. The workflow of tasks processed in the computing system assumes that there are many sources of input data and many destinations of output data, i.e., many-to-many transmissions are used in the system. The addressed optimization problem is formulatedin the form of an ILP (Integer Linear Programing) model. Since the model is computationally demanding and NP-complete, besides the branch-and-bound algorithm included in the CPLEX solver, we propose additional cut inequalities. Moreover, we present and test two effective heuristic algorithms: tabu search and greedy. Both methods yield satisfactory results close to optimal.

In wireless mobile networks, a client can move between different locations while staying connected to the network and access the remote server over the mobile networks by using their mobile de- vices at anytime and anywhere. However, the wireless network is more prone to some security attacks, as it does not have the ingrained physical security like wired networks. Thus, the client authentication is required while accessing the remote server through wireless network. Based on elliptic curve cryptosystem (ECC) and identity-based cryptography (IBC), Debiao et al. proposed an ID-based client authentication with key agreement scheme to reduce the computation and communication loads on the mobile devices. The scheme is suitable for mobile client-server environments, is secure against different attacks and provides mutual authentication with session key agreement between a client and the remote server as they claimed. Unfotunately, this paper demonstrates that Debiao et al.’s scheme is vulnerable some cryptographic attacks, and proposed an improved ID-based client authentication with key agreement scheme using ECC. The proposed scheme is secure based on Elliptic Curve Discrete Logarithm Problem (ECDLP) and Computational Diffie-Helmann Problem (CDHP). The detail analysis shows that our scheme overcomes the drawbacks of Debiao et al.’s scheme and achieves more functionality for the client authentication with lesser computational cost than other schemes.

Some data sets contain data clusters not in all dimension, but in subspaces. Known algorithms select attributes and identify clusters in subspaces. The paper presents a novel algorithm for subspace fuzzy clustering. Each data example has fuzzy membership to the cluster. Each cluster is defined in a certainsubspace, but the the membership of the descriptors of the cluster to the subspace (called descriptor weight) is fuzzy (from interval [0,1]) – the descriptors of the cluster can have partial membership to a subspace the cluster is defined in. Thus the clusters are fuzzy defined in their subspaces. The clusters are defined by their centre, fuzziness and weights of descriptors. The clustering algorithm is based on minimizing of criterionfunction. The paper is accompanied by the experimental results of clustering. This approach can be used for partition of input domain in extraction rule base for neuro-fuzzy systems.

This paper presents non-linear mathematical model of a computer network with a part of wireless network. The article contains an analysis of the stability of the network based on TCP-DCR, which is a modification of the traditional TCP. Block diagram of the network model was converted to a form in order to investigate the D-stability using the method of the space of uncertain parameters. Robust D-stability is calculated for constant delays values.