Dritan Kaleshi

Performance comparison of cooperative and non-cooperative relaying mechanisms in wireless networks

Relaying is a known method for increasing coverage in wireless communication systems. In addition to coverage increase, new cooperative relaying methods have been proposed that may increase the wireless system capacity by taking advantage of higher data rates in intermediate cooperating relaying nodes. This paper investigates the performance of several of these relaying methods in terms of maximum achievable throughput at MAC service access point for single-frequency wireless ad-hoc networks. The simulation framework used is described, and the performance limitations of the relaying methods are analysed. We find that relaying, cooperative or not, does not significantly increase maximum achievable throughput for line-of-sight (LOS) propagation environments. The achievable throughput can be significantly increased for non-line of sight (NLOS) environments under specific conditions for source/destination and intermediate relaying nodes

A multi-modal sensor infrastructure for healthcare in a residential environment

Ambient Assisted Living (AAL) systems based on sensor technologies are seen as key enablers to an ageing society. However, most approaches in this space do not provide a truly generic ambient space - one that is not only capable of assisting people with diverse medical conditions, but can also recognise the habits of healthy habitants, as well as those with developing medical conditions. The recognition of Activities of Daily Living (ADL) is key to the understanding and provisioning of appropriate and efficient care. However, ADL recognition is particularly difficult to achieve in multi-resident spaces; especially with single-mode (albeit carefully crafted) solutions, which only have limited capabilities. To address these limitations we propose a multi-modal system architecture for AAL remote healthcare monitoring in the home, gathering information from multiple, diverse (sensor) data sources. In this paper we report on developments made to-date in various technical areas with respect to critical issues such as cost, power consumption, scalability, interoperability and privacy.

Sparse Malicious False Data Injection Attacks and Defense Mechanisms in Smart Grids

This paper discusses malicious false data injection attacks on the wide area measurement and monitoring system in smart grids. First, methods of constructing sparse stealth attacks are developed for two typical scenarios: 1) random attacks in which arbitrary measurements can be compromised; and 2) targeted attacks in which specified state variables are modified. It is already demonstrated that stealth attacks can always exist if the number of compromised measurements exceeds a certain value. In this paper, it is found that random undetectable attacks can be accomplished by modifying only a much smaller number of measurements than this value. It is well known that protecting the system from malicious attacks can be achieved by making a certain subset of measurements immune to attacks. An efficient greedy search algorithm is then proposed to quickly find this subset of measurements to be protected to defend against stealth attacks. It is shown that this greedy algorithm has almost the same performance as the brute-force method, but without the combinatorial complexity. Third, a robust attack detection method is discussed. The detection method is designed based on the robust principal component analysis problem by introducing element-wise constraints. This method is shown to be able to identify the real measurements, as well as attacks even when only partial observations are collected. The simulations are conducted based on IEEE test systems.

Performance investigation of IEEE 802.11 MAC in multihop wireless networks

Medium access control (MAC) protocols have a large impact on the achievable system performance for wireless ad hoc networks. Because of the limitations of existing analytical models for ad hoc networks, many researchers have opted to study the impact of MAC protocols via discrete-event simulations. However, as the network scenarios, traffic patterns and physical layer techniques may change significantly, simulation alone is not efficient to get insights into the impacts of MAC protocols on system performance. In this paper, we analyze the performance of IEEE 802.11 distributed coordination function (DCF) in multihop network scenario. We are particularly interested in understanding how physical layer techniques may affect the MAC protocol performance. For this purpose, the features of interference range is studied and taken into account of the analytical model. Simulations with OPNET show the effectiveness of the proposed analytical approach.

Residential energy demand management in smart grids

This paper studies a coordination mechanism based on heuristic rules to manage the energy demand in a residential smart grid scenario and evaluates the survivability of the system when failures occur in the communication infrastructure. This is achieved by modeling residential demand response considering Plug-in Hybrid Electric Vehicles (PHEVs) as part of the loads, local renewable generation capability and variable energy pricing based on a Time of Use (TOU) scheme. A mathematical model of the system is built based on realistic data, and the evaluation of the survivability of the system is carried out using Monte Carlo simulations and statistical experiment design techniques, where the probability of overloading the distribution system is derived for different scenarios. Results obtained show that the coordination mechanism is able to achieve energy efficiency and cost saving for residential users when the energy consumption is managed properly. At the same time the probability of overloading the distribution system can be reduced. The efficiency and economic savings depend on the potential of renewable sources in the region considered and the survivability of the system depends on a reliable communication infrastructure.

Classification and suitability of sensing technologies for activity recognition

Wider availability of sensors and sensing systems has pushed research in the direction of automatic activity recognition (AR) either for medical or other personal benefits e.g. wellness or fitness monitoring. Researchers apply different AR techniques/algorithms and use a wide range of sensors to discover home activities. However, it seems that the AR algorithms are purely technology-driven rather than informing studies on the type and quality of input required. There is an expectation to over-instrument the environment or the subjects and then develop AR algorithms, where instead the problem should be approached from a different angle i.e. what sensors (type, quality and quantity) a given algorithm requires to infer particular activities with a certain confidence? This paper introduces the concept of activity recognition, its taxonomy and familiarises the reader with sub-classes of sensor-based AR. Furthermore, it presents an overview of existing health services Telecare and Telehealth solutions, and introduces the hierarchical taxonomy of human behaviour analysis tasks. This work is a result of a systematic literature review and it presents the reader with a comprehensive set of home-based activities of daily living (ADL) and sensors proven to recognise these activities. Apart from reviewing usefulness of various sensing technologies for home-based AR algorithms, it highlights the problem of technology-driven cycle of development in this area.

The power of data: Data analytics for M2M and smart grid

Machine to machine (M2M) communication has been gaining momentum in recent years as a key enabling technology for a wide range of applications including smart grid, e-health, home/industrial automation, and smart cities. However, with the current communication systems mainly optimized for human to human communications, there are important capabilities that need to be developed in M2M systems in order to fully realize the new smart services enabled by M2M. In this paper, we provide an overview of M2M and its applications to smart grid. In particular, we discuss technical areas where data mining and machine learning can play an important role in realizing various smart functionalities in the future power grid. As a case study, we also present a novel phase identification technique in smart grid based on smart meter data. Preliminary results have demonstrated the effectiveness of the proposed algorithm.

Modeling Link Adaptation Algorithm for IEEE 802.11 Wireless LAN Networks

Link adaptation is a critical component of IEEE 802.11 systems. In this paper, we analytically model a retransmission based Auto Rate Fallback (ARF) link adaptation algorithm. Both packet collisions and packet corruptions are modeled with the algorithm. The models can provide insights into the dynamics of the link adaptation algorithms and configuration of algorithms parameters. It is also observed that when the competing number of stations is high, packet collisions can largely affected the performance of ARF and make ARF operate with the lowest date rate, even when no packet corruption occur. This is in contrast to the existing assumption that packet collision will not affect the correct operation of ARF and can be ignored in the evaluation of ARF. The work presented in this paper can provide guidelines on configuring the link adaptation algorithms and designing new link adaptation algorithms for future high speed 802.11 systems.

Ensuring interoperability in a home networking system: a case study

One of the main problems in home networked systems is the wide diversity of technologies, application requirements and cost allowance for devices and systems in general. This is translated to a division into different islands of technology that goes down to single manufacturer systems, thus blocking the way to the system integration as the main reason for the existence of the network. It is widely accepted that achieving the interworking is the most important aspect of a system specification. Object-oriented modelling associated with proper application management mechanisms for trading and binding provides the best approach to standardisation work on home systems interworking. We take here as an example the work toward an interoperability specification for an energy management system. The system described spans several communication media and brings together several consumer and producer entities. The system aims to provide increased comfort while either minimising the usage of resources or their cost for the same level of usage. Results from installed and running systems show the success of the approach.

An Analysis of the Impact of Out-of-Order Recovery Algorithms on MPTCP Throughput

In this paper we evaluate and compare the end-to-end performance of different multipath TCP (MPTCP) congestion controllers when run in conjunction with different TCP packet reordering recovery algorithms. The paper answers the following questions: what is the impact of out-of-order events on the end-to-end throughput when using MPTCP, how do out-of-order recovery algorithms that have been proposed for single-path TCP perform with multi-path TCP, and how sensitive this performance is against the delay difference between the paths used. The paper compares three different MPTCP congestion control algorithms used in conjunction with four current TCP packet reordering solutions: D-SACK, Eifel, TCP-DOOR, and F-RTO. Simulation results show that whilst TCP-DOOR and, second, D-SACK perform generally better across all congestion control MPTCP implementations, the choice of packet reordering algorithm is not always fixed and straightforward - when MPTCP is used with some form of coupled congestion control the performance degrades towards that of single-path usage when the delay difference of the paths is over 200ms. The paper identifies combinations of congestion control and packet reordering algorithms that give better aggregate throughput performance for different path delay differences.