- QoS provision for multimedia communication
- Video streaming
- Multimedia communication and high-speed networks
- Multimedia networking
- ACSE protocols for multimedia communication
- Mobile Ad hoc NETworks (MANETs)
- Wireless Sensor Networks (WSNs)
- Multimedia Intelligence and Intelligent information systems
- Intelligent Web Services, Intelligent browsing
- User profiling and context-awareness
- Semantic Web and Knowledge management
- Semantic modeling and Ontological representation
- e-Learning technologies
Video and audio are becoming increasingly popular on the Internet and are being accessed by a variety of networked devices through either wired or wireless links. Many distributed multimedia applications have been created, including Internet telephony, Internet videoconferencing, on-demand streaming or broadcasting, IPTV, multimedia messaging, distance learning, gaming and entertainment, and so forth. Streaming real-time and on-demand audio and video over the Internet, local and wide area wireless networks are becoming a mainstream means of communication. To accelerate the adoption of these new emerging applications, various issues must be addressed such as the architecture and design of multimedia communication systems, the quality-of-service (QoS) provisioning, the network and content security, etc.
MOBILE AD HOC NETWORKS (MANETs)
Wireless ad hoc networks or mobile ad hoc networks (MANETs) maintain the general characteristics of wireless networks, while including additional properties and restrictions. In the infrastructure wireless network there exists some fixed topology. However, in ad hoc networks, due to the movement of the nodes and the resulting route failures and recomputations, difficulty in maintaining sessions, etc., their topology changes dynamically. In addition, ad hoc networks have no central controller. In most cases, each node is responsible for maintaining the information of delay, jitter, loss rate stability, and distance for each link in order to feed routing algorithms. However, this state information is inherently imprecise due to the changes in the topology and the fact that resources such as bandwidth, battery, processing, and storage are limited. These peculiar characteristics of MANETs complicate QoS provision, and thus multimedia communication. In the last decade, many research efforts have been obtained to realize various challenges, such as:
1) Effective routing protocols and congestion control mechanisms for MANETs;
2) Effective TDMA scheduling algorithms that guarantee QoS provisioning over MANETs by reducing the end-to-end delay and drop rate,
3) Video streaming over MANETs etc...
- QoS Routing over MANETs: A lot of intensive research has been carried out in the direction of providing multimedia communication over wireless mobile ad hoc network (MANET). In MANET, various QoS problems exist such as inefficient routing, handling node mobility, power conservation, limited processing capabilities of network devices, high error rates. Wireless routing introduces new challenges as applying basic routing algorithms directly on MANET could lead to large power consumption, interference, and loadbalancing problems. Many routing algorithms have been proposed as extensions to the basic routing algorithms to enhance their performance in MANETs. The following article summarizes existing solutions on QoS routing and resource reservation mechanisms in order to provide multimedia communication over MANET. It also considers the limitations of existing QoS models with regard to satisfying QoS in serving multimedia over MANET. The newest QoS architectures give much better results in providing QoS support. However, more refinements must be proposed in order to enhance further their performance in MANETs.
- Kanellopoulos, D. (2017). QoS routing for multimedia communication over wireless mobile ad hoc networks: A survey. International Journal of Multimedia Data Engineering and Management Vol. 8, No. 1, pp.42-71. (PDF)
- Congestion control: In a MANET, there is no need to deploy any infrastructure to make nodes to communicate with each other. MANETs have peculiar characteristics that complicate congestion control. The standard TCP congestion control mechanism is not able to handle the special properties of a shared wireless multi-hop channel well. The frequent changes of the network topology and the shared nature of the wireless channel pose significant challenges. Therefore, we must analyze the design challenges for an enhanced transport protocol (i.e.,TCP enhancements for wireless links) and we must propose effective congestion control schemes for MANETs.
- Kanellopoulos D. Congestion control for MANETs: An overview. ICT Express (Elsevier).
- Scheduling for MANETs: MANETs use algorithms that schedule transmissions in a fair and efficient manner. A multi-hop scheduler schedules transmissions so that the channel utilization is maximized while guaranteeing the quality of service (QoS) for all nodes. QoS-based scheduling in MANETs must be obtained under time-critical conditions as these networks have several features that produce unique queuing dynamics. Schedulers in MANETs take into account various QoS parameters such as end-to-end packet delay, packet delivery ratio, flow priority etc. Also, scheduling in MANETs takes many forms such as distributed priority, fair, opportunistic, etc. The following article provides a survey of scheduling techniques for MANETs and discusses advantages and disadvantages of each category.
- Kanellopoulos D. Recent progress on QoS scheduling for mobile ad hoc networks. Journal of Organizational and End User Computing.
WIRELESS SENSOR NETWORKS (WSNs)
WSNs are used in various application areas such as ecological monitoring, traffic control, healthcare, and industrial automation. A WSN contains sensor nodes that can sense the physical environment for data acquisition, data computation, and communication. A sensor node has limited processing capabilities and contains signal-processing circuits, microcontrollers, and wireless transmitters or receiver antennas. Sensor nodes send their collected data to the base station (BS), if the BS is within communication range. Otherwise, the data are sent to other sensor nodes through routing protocols. The batteries of the sensor nodes do not require recharging from the time these nodes are randomly deployed in the sensing fields. Therefore, prolonging the lifespan of a WSN is a hot research topic. Various energy efficiency techniques can prolong the lifespan of WSNs, such as the following:
- Energy-efficient routing protocols
- Duty-cycling and medium access control (MAC) protocols.
- Topology control
- Energy efficient data aggregation schemes.
- Cross-layer optimization techniques.
Routing techniques affect the energy conservation of sensor nodes since the communicating module of a sensor node consumes considerably more energy than the computing module. The energy consumed during communication mostly depends on the distance between the sending and the receiving nodes. Therefore, many routing solutions have been proposed on how to optimize the distance. The majority of clustering algorithms randomly select several sensor nodes as CHs. This random selection of CHs causes uneven energy consumption. Consequently, the energy load on every sensor node should be balanced in order to avoid a reduction of network lifespan. Many factors, such as the number of cluster members and their distance to the BS, can impact on the energy consumption of CHs. Also, from a global viewpoint, the energy dissipation of the network is affected by the distribution of the CHs. The location of CHs affects network lifetime significantly. By relocating the CHs to better locations, network load can be balanced and lifetime can be prolonged. From another viewpoint, the ability of the sensors to sense a particular phenomenon is spatially limited. Most of the sensors must be in their location most of the time.
Popovic G., Djukanovic G. and Kanellopoulos D. (2018) “Cluster Head Relocation Based on Selfish Herd Hypothesis for Prolonging the Life Span of Wireless Sensor Networks”. Electronics (MDPI), 7(12): 403. Impact Factor: 2.110 (2017).