Chrysostomos Chrysostomou

Key issues for the design and development of mobile commerce services and applications

This paper suggests a new approach for developing m-commerce services and applications based on a scheme that divides m-applications into directory- and transaction-oriented classes, identifies mobile user requirements, and takes into consideration the constraints of current technologies for mobile and wireless computing. The efficacy of the proposed approach in a real scenario is discussed.

Congestion control in differentiated services networks using Fuzzy-RED

Network congestion control remains a critical and high priority issue. The rapid growth of the Internet and increased demand to use the Internet for time-sensitive voice and video applications necessitate the design and utilization of effective congestion control algorithms, especially for new architectures, such as differentiated services (Diff-Serv). As a result, a number of researchers are now looking at alternative schemes to TCP congestion control. Random early detection (RED) and its variants are one of these alternatives to provide quality of service (QoS) in TCP/IP Diff-Serv networks. In this paper, we present the results of a fuzzy logic control approach to RED implementation, Fuzzy-RED, implemented within the Diff-Serv framework. The proposed fuzzy logic approach for congestion control allows the use of linguistic knowledge to capture the dynamics of non-linear probability discard functions and offer more effective implementation, use multiple inputs to capture the (dynamic) state of the network more accurately, enable finer tuning for packet discarding behaviors for aggregated flows, and thus provide better QoS to different types of data streams, such as TCP/FTP traffic or TCP/Web-like traffic, whilst maintaining high utilization.

Fuzzy logic controlled RED: congestion control in TCP/IP differentiated services networks

The use of the Internet for time-sensitive services, such as voice and video applications, requires a predictable quality of service. The TCP/IP differentiated services (Diff-Serv) architecture was introduced to achieve such performance. Network congestion control, however, still remains a critical and high priority issue. A number of researchers are looking at alternative schemes such as random early detection (RED) and its variants to handle congestion. In this paper we present the results of a fuzzy logic control approach to the implementation of RED – Fuzzy-RED. We believe that with fuzzy logic we are able to use linguistic knowledge to implement better understood nonlinear probability discard functions, achieve better differentiation for packet discarding behaviors for aggregated flows, and so provide better quality of service to different kinds of traffic whilst maintaining high utilization.

Fuzzy explicit marking for congestion control in differentiated services networks

This paper presents a new active queue management scheme, fuzzy explicit marking (FEM), implemented within the differentiated services (Diffserv) framework to provide the congestion control using a fuzzy logic control approach. Network congestion control remains a critical and high priority issue. The rapid growth of the Internet and increased demand to use the Internet for time-sensitive voice and video applications necessitate the design and utilization of effective congestion control algorithms, especially for new architectures, such as Diffserv. As a result, a number of researchers are now looking at alternatively schemes to TCP congestion control. RED (random early detection) and its variants are one of these alternatives to provide quality of service (QoS) in TCP/IP Diffserv networks. The proposed fuzzy logic approach for congestion control allows the use of linguistic knowledge to capture the dynamics of nonlinear probability marking functions and offer effective implementation, use of multiple inputs to capture the (dynamic) state of the network more accurately, enable finer tuning for packet marking behaviors (either dropping a packet or setting its ECN - explicit congestion notification - bit) for aggravated flows, and thus provide better QoS to different types of data streams, such as TCP/FTP traffic or TCP/Web-like traffic, whilst maintaining high utilization.

Applying adaptive QoS-aware medium access control in priority-based vehicular ad hoc networks

This paper proposes a novel, adaptive medium access control mechanism for vehicular ad hoc networks. A simple, effective, and efficient nonlinear control law is built, based on fuzzy logic control principles, which can be easily adopted in different network environments (e.g. vehicle-to-vehicle (V2V) communication and vehicle-to-infrastructure (V2I) communication). We demonstrate, via simulative evaluation, that the proposed fuzzy control methodology offers inherent robustness with effective control of the system under dense and dynamic conditions, without the need to (re)tune any parameters. The proposed approach offers distinct differentiation among differently prioritized traffic types, thus providing adequate Quality of Service (QoS) in terms of throughput performance, in contrast with the IEEE 802.11p MAC protocol we compared against.

Internet of Things: Security vulnerabilities and challenges

Internet of Things (IoT) has been given a lot of emphasis since the 90s when it was first proposed as an idea of interconnecting different electronic devices through a variety of technologies. However, during the past decade IoT has rapidly been developed without appropriate consideration of the profound security goals and challenges involved. This study explores the security aims and goals of IoT and then provides a new classification of different types of attacks and countermeasures on security and privacy. It then discusses future security directions and challenges that need to be addressed to improve security concerns over such networks and aid in the wider adoption of IoT by masses.

Congestion control in differentiated services networks using fuzzy logic

The provision of quality of service (QoS) in a differentiated services (Diff-Serv) environment requires an adequate differentiation between high-priority/assured and low-priority/best-effort classes of service in the presence of congestion, giving priority/preference to assured-tagged traffic. For this purpose, a new active queue management scheme, implemented within the Diff-Serv framework, is presented that provides congestion control in TCP/IP networks using a fuzzy logic control approach. The proposed fuzzy logic approach for congestion control allows the use of linguistic knowledge to capture the dynamics of nonlinear probability marking functions, uses multiple inputs to capture the dynamic state of the network more accurately, and can offer effective implementation. A simulation study over a wide range of traffic conditions - considering multiple bottleneck links - shows that the fuzzy logic based controller outperforms the random early detection (RED) implementation for Diff-Serv in terms of link utilization, packet losses, and queue fluctuations and delays. Also, the proposed scheme can offer better differentiation among assured and best-effort traffic, thus it can provide better QoS to different types of data streams, such as TCP/FTP traffic or TCP/Web-like traffic, whilst maintaining high utilization.

Overview of Fuzzy-RED in Diff-Serv Networks

The rapid growth of the Internet and increased demand to use the Internet for time-sensitive voice and video applications necessitate the design and utilization of new Internet architectures with effective congestion control algorithms. As a result the Diff-Serv architectures was proposed to deliver (aggregated) QoS in TCP/IP networks. Network congestion control remains a critical and high priority issue, even for the present Internet architecture. In this paper we present Fuzzy-RED, a novel approach to Diff-Serv congestion control, and compare it with a classical RIO implementation. We believe that with the support of fuzzy logic, we are able to achieve better differentiation for packet discarding behaviors for individual flows, and so provide better quality of service to different kinds of traffic, such as TCP/FTP traffic and TCP/Weblike traffic, whilst maintaining high utilization (goodput).

Fuzzy Logic Congestion Control in TCP/IP Tandem Networks

Network resource management and control is a complex problem that requires robust, possibly intelligent, control methodologies to obtain satisfactory performance. While many Active Queue Management (AQM) mechanisms have been introduced to assist the TCP congestion control, these require careful configuration of non-intuitive control parameters, and show weaknesses to detect and control congestion under dynamic traffic changes, and a slow response to regulate queues. Furthermore, there is also a need to evaluate thoroughly the performance of such mechanisms for tandem networks containing multiple congested routers. A new AQM scheme, Fuzzy Explicit Marking (FEM) has recently been proposed to provide congestion control in TCP/IP best-effort networks using a fuzzy logic control approach. We present the control approach followed by the FEM controller, and evaluate the performance of FEM and a number of representative AQM schemes (A-RED, PI and REM) in a tandem network. An extensive simulation study over a wide range of traffic conditions shows that the FEM controller outperforms the other schemes in terms of queue fluctuations and delays, packets losses, link utilization, and speed of response to regulate queues.

On the efficient use of multiple channels by single-receiver clients in wireless data broadcasting

This letter proposes an adaptive wireless push system for wireless data broadcasting environments, where multiple channels are available for broadcasting data from a broadcast server to a large number of mobile clients. We address the general case where the client demands are not dependent on client locations. The efficiency of the proposed system lies in the fact that it offers significant performance improvements to the system clients with the need of only one receiver at each client device. Copyright