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M U LT I M E D I A I N W I R E L E S S /M O B I L E A D H O C N E T W O R K S
QOS-AWARE TDMA FOR END-TO-END TRAFFIC SCHEDULING IN AD HOC NETWORKS DIMITRIOS D. VERGADOS, UNIVERSITY OF THE AEGEAN DIMITRIOS J. VERGADOS, NATIONAL TECHNICAL UNIVERSITY OF ATHENS CHRISTOS DOULIGERIS, UNIVERSITY OF PIRAEUS SPYRIDON L. TOMBROS, APEX AG, SWITZERLAND
ABSTRACT
The proliferation of low-cost broadband air interfaces has paved the way to the introduction of high-definition multimedia services in mobile and wireless networks. The cost for network resources utilization, when provisioning such services, will play a prominent role in their commercial success. 68
The proliferation of low-cost broadband air interfaces has paved the way to the introduction of high-definition multimedia services in mobile and wireless networks. The cost for network resources utilization, when provisioning such services, will play a prominent role in their commercial success, since the more spare resources that can be used, the more cheaply the services can be delivered to the end users. In the context of promoting the role of ad hoc networks as service platforms for high quality multimedia applications, this article first discusses and classifies a set of issues involved in quality of service (QoS) provisioning in ad hoc networks and then presents a congestion-free TDMA algorithm for end-to-end network resources assignment via an optimized mechanism that relies on capacity requests and grants. The article also illustrates a method for invoking this algorithm to achieve efficient end-to-end QoS provisioning and concludes by showing the superiority of the proposed algorithm, as compared to other recently proposed TDMA scheduling algorithms.
INTRODUCTION Mobile ad hoc networks (MANETs) are peer-topeer self-organized networks formed by a set of stations that are within range of each other. Every node in ad hoc networks functions both as a host and as a router, exhibiting also a capability for movement. Ad hoc networks consist of autonomous nodes. The routing of packets relies on multihop principles. The network topology is dynamic due the requirement for having moving nodes. Quality of service (QoS) provisioning in ad hoc networks can be implemented in many ways. The particular choice of implementation depends on the provided QoS, the nature of the flow, the scope of the traffic reservation, and the manner that the QoS requirements are quantified. Also, the specific characteristics of an ad hoc network
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topology influence the network and the MAC layers’ QoS mechanisms, leaving higher-layer protocols intact. In addition, a suitable end-toend QoS for multimedia communications can be realized through the admission control mechanism that can ensure that each flow receives the desired level of QoS, thus enabling guaranteed QoS along the entire transmission path. Various schemes have been proposed in the literature for end-to-end QoS provisioning in ad hoc networks [1, 2]. These schemes are mostly related to TCP adaptable transport protocols that react to congestion events. Also, MAC-level resource allocation schemes, like the one presented in [3], require the total network traffic not to exceed a predefined threshold. However, all these schemes rely on the ability to first detect and then deal with congestions. QoS scheduling schemes [4–8] have also been designed for TDMA slot assignment in ad hoc networks. These algorithms opt to solve the NPcomplete broadcast scheduling problem in order to create an optimal TDMA schedule for every node in the network. Since multimedia delivery can be enhanced by the application of QoS reservation schemes, the TDMA scheduling can be utilized as the foundation for reservations. However, these schemes face serious limitations (centralized and static nature, high end-to-end delay) with regard to end-to-end QoS preservation. This article presents a new distributed dynamic end-to-end TDMA scheduling algorithm (DDETSA) that overcomes these issues. This article is organized as follows. The current methods applied for QoS reservation in ad hoc networks, including mechanisms for call admission control and end-to-end scheduling, are presented. Following, the design of the congestion-free TDMA algorithm is described, and our approach for supporting QoS-aware ad hoc network communications is presented. An analysis of the proposed algorithm is performed, draw comparisons with contemporary TDMA scheduling algorithms. Finally, the obtained performance results are summarized.
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QoS provisioning
Provided QoS
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■ Figure 1. QoS provisioning classifications.
QOS IN AD HOC NETWORKS QOS PROVISIONING FOR AD HOC NETWORKS QoS provisioning in ad hoc networks can be implemented in a number of different ways, depending on the provided QoS, the nature of the flow, the scope of the reservation, and the manner in which the QoS requirements are quantified, as illustrated in Fig. 1. A network can provide guaranteed QoS to a flow, when all QoS parameters this flow receives by the network have deterministic bounds, and statistical QoS, when the QoS parameters provided to it do not have deterministic bounds, but they can be known with a good probability. Variable bounds QoS provisioning can be considered as a hybrid method between guaranteed and statistical provisioning, and can be used for connections that transport traffic at variable rates. Depending on the nature of each flow, QoS provisioning can be divided into per connection and per class provisioning. QoS provisioning can be applied either per-hop or end-to-end. End-toend reservations are made when the QoS parameters refer to the path from the source to the destination. In per-hop QoS provisioning the QoS parameters refer to each hop separately. In order to implement end-to-end reservations on a network, a mechanism for providing per-hop reservations is required. Finally, QoS reservations can be made either in an absolute or in a proportional manner. An absolute QoS reservation is defined by a set of absolute QoS parameters, whereas the proportional QoS provisioning mechanisms try to maintain the service level of the separate flows at a predefined ratio.
AD HOC ADMISSION CONTROL Admission control is a key feature in securing end-to-end QoS reservation by offering the means to avoid traffic congestion. The admission control mechanism can ensure that each accepted flow receives the desired level of QoS and thus enables guaranteed QoS along the entire transmission path. The admission control mechanism in a wireless ad hoc network consists of two separate operations. The first operation is responsible for the classification and conditioning of the arriving traffic and the second operation determines the service-level agreements (SLAs) that can be accepted by the network without violating the QoS parameters of the existing flows. In this context, the wireless channel cannot be considered as a link, because the number of
IEEE Wireless Communications • October 2006
users who can access the channel changes with respect to the distance between the users. Endto-end QoS in ad hoc networks can be provided only after guaranteed per-hop QoS has been applied. The use of QoS routing algorithms and appropriate redundancy of resources is necessary. The use of the TDMA MAC protocol that can provide bandwidth and delay guarantees in a per-hop basis can be perceived as the basis for the delivery of end-to-end QoS that will allow multimedia transmissions. The estimation of the QoS provided by each hop in an ad hoc network is not a trivial task. While in wired networks the bandwidth, delay, and jitter parameters of each link are static, in a wireless network node mobility and variable noise make the estimation of the per-hop QoS difficult. In this environment, not only the delay and bandwidth, but also the link stability, the used power, and so forth should be considered. Thus, the TDMA scheduling schemes that can provide guaranteed bandwidth for a static scenari may prove to be inefficient in cases where node mobility is considered. Therefore, the ad hoc network should be able to follow up node movements that will allow it to back up resources for deployment on alternative paths. Also, the addition of extra ad hoc nodes may have an effect in the QoS perceived by the users. Finally, the admission control problem for end-to-end QoS in multimedia ad hoc networks is correlated to the routing algorithms used. Proactive routing protocols do not seem appropriate, because the diffusion of the available resources at each link may cause inefficiency and inaccuracy. Therefore, the reactive nature of ondemand routing protocols seems to be the most appropriate.
QoS reservations can be made either in an absolute or in a proportional manner. An absolute QoS reservation is defined by a set of absolute QoS parameters, whereas the proportional QoS provisioning mechanisms try to maintain the service level of the separate flows at a predefined ratio.
END-TO-END QOS SCHEDULING As mentioned above, ad hoc networks are characterized by the absence of guaranteed resources and by a variable infrastructure. Users are informed in real time about the resources of the network (i.e., bandwidth and transmission-duration slot time) and can also demand more bandwidth in cases where applications exceed those preallocated by the network capacity. In such a volatile environment, TDMA may constitute the best solution. However, the application of timeslot-reservation medium access control in ad hoc networks leads to the broadcast scheduling problem (BSP). BSP is a well-known NP-complete problem that consists of finding the minimal partition between
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Taking into consideration the above issues, we propose a new distributed dynamic end-toend scheduling algorithm (DDETSA) that allows dynamic slot assignment in a distributed fashion and at the same time reduces the end-to-end delay. Its performance is evaluated and compared to the previously proposed TDMA algorithms MFA and HNN-GA.
THE PROPOSED SYSTEM MOTIVATION Free
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■ Figure 2. TDMA based slot reservation. vertices in a graph with the limitation that every vertex belongs in at least one partition and every partition does not contain any neighboring vertices or vertices with common neighbors [4]. Various techniques have been developed for achieving TDMA scheduling by solving the BSP, such as “mean field annealing” (MFA) [5]. In [6], a backtracking sequential coloring algorithm was used to obtain a minimal TDMA frame length and the corresponding transmission assignments. The noisy chaotic neural network was used to find the maximum node transmissions. The BSP was solved in [7] using a selforganizing distributed algorithm via only local collaborative interactions among neighboring network stations. In [8], an algorithm that combines a Hopfield neural network for obtaining the minimum frame length and a genetic algorithm for achieving a maximal throughput (HNN-GA) was proposed. All of the above schemes present a number of limitations that have prevented their deployment. The main limitations are the following: • Most of the proposed TDMA scheduling schemes are centralized and thus cannot be efficiently deployed in ad hoc network scenarios. Also, even the distributed algorithms that rely on local exchange of information require the processed scheduling information to be propagated throughout the network in order to create the necessary collision free schedule. • All these algorithms assign the TDMA slots statically (i.e., without taking into consideration the bandwidth requirements at each node and the delay characteristics of every communication flow). After the slot allocation is completed, every node is assigned to a number of slots for transmitting. Thus, some slots may have been allocated to nodes that do not have any packets to transmit, while neighboring nodes, loaded with traffic, would be prevented from transmitting. • The TDMA frames are produced for every node in the network without taking into account the routing paths that are used for transmitting the information. Thus, every packet that is received by an intermediate forwarding node must have to wait for a long time before it is forwarded to its next hop destination. This causes an increase in the end-toend delay.
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The delivery of real-time multimedia traffic can have a tremendous impact on the deployment rate of ad hoc networks implementations. The introduction of the capability to transfer efficiently multimedia traffic in ad hoc networks can be viewed as a high priority. The guaranteed QoS requirements of multimedia traffic over ad hoc networks make the TDMA MAC protocol a natural solution for bandwidth reservations. However, the current state of the art in TDMA scheduling for ad hoc networks is limited to algorithms that try to maximize the total number of transmission opportunities for the nodes in the network, while maintaining the minimum frame length. This kind of slot allocation is not suitable for providing end-to-end QoS for multimedia traffic, because the per-node allocation does not take into account the added delay caused by the subsequent forwarding in the ad hoc networks. Endto-end TDMA scheduling tries to assign time slots to every connection in a way that can satisfy the delay and bandwidth requirements of the multimedia traffic through the entire path from the source to the destination. The dynamic nature of multimedia connections requires that slot allocations do not depend in a static way only on the network topology. On the contrary, the end-to-end limitations for guaranteed QoS require that the TDMA based reservations are made according to the traffic requirements at any given time.
ALGORITHM/SYSTEM DESCRIPTION DDETSA, the TDMA algorithm presented in this article, ensures guaranteed QoS for end-toend communications. This is accomplished through timeslot reservations for all the nodes in the path from the source to the destination node. We assume that multiple access in the wireless channel is achieved by TDMA. A number of nodes can transmit in every TDMA slot. The number of slots needed for every node to have an opportunity to transmit is called the TDMA frame length. Assuming that every node has only one transmission opportunity in every frame, the access delay is equal to the frame length. Obviously the network capacity increases as the number of nodes in every slot increases. One needs to determine which slot should be used by each ad hoc node for transmitting and which slots should be used for listening. Collision avoidance requires that the first ad hoc nodes in the path should be assigned in timeslots earlier than the ad hoc nodes that follow. On the other hand, collisions can be avoided if the nodes, which receive packets at the same
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time, are not one-hop neighbors (TDMA does not suffer from the exposed terminal situation). Moreover, possible transmissions to the same destination should be assigned in different time slots. Nodes that are not one-hop neighbors should receive (if possible) at the same time, in order to minimize the total frame length [9]. We represent all ad hoc nodes as vertices of a graph with edges existing between nodes only when they are within the transmission range. There are no collisions in the network, if the distance of all transmitting nodes in the graph is at least two hops. So, the broadcast scheduling problem is to determine how to schedule every node in the network into the appropriate slot, so that the maximum capacity is achieved in the shortest possible frame length. Both distributed and centralized algorithms may be introduced to solve this problem of TDMA scheduling. Even though centralized algorithms can produce more effective TDMA schedules, distributed scheduling schemes are more suitable for wireless ad hoc networks, since they allow more flexibility. When the centralized approach is used, a node in the ad hoc network (e.g., the gateway) gathers the connectivity information between all the ad hoc nodes in the network and uses existing energy-efficient routing algorithms to calculate the paths from every ad hoc node to the gateway. Then, the gateway constructs a TDMA frame that ensures collision avoidance. This schedule is broadcasted back to the ad hoc nodes, allowing them to know when they can transmit or receive a packet. On the other hand, if a distributed TDMA scheduling scheme is used, the TDMA frame is constructed locally, based on information exchanged between neighbors. More specifically, during the path setup phase, the on-demand routing packets are piggybacked with information regarding the available slots for transmission and reception at locations of the intermediate forwarding nodes, thus allowing the estimation of the end-to-end delay for the examined path. The optimal path is then selected and the abovementioned slots are allocated for the specific transmission. Every ad hoc node uses the TDMA frame information to calculate the exact time when it can transmit and when it should expect the reception of a packet.
PER NODE VS. PER PATH SCHEDULING Most TDMA scheduling schemes operate in a per-hop basis. Thus the transmitting ad hoc node should wait for the arrival of the appropriate wake-up time of its next-hop destination before it transmits the data. Then, the forwarding ad hoc node should wait for the wake-up time of the next ad hoc node in the path, before it transmits the data, and so on, until the message finally reaches the ad hoc gateway. This strategy leads to end-to-end delay times that are proportional to the number of intermediate forwarders and proportional to the TDMA frame interval. Also, these strategies assign a fixed number of slots for every node to transmit and do not support dynamic slot assignment, making them inappropriate for multimedia transmissions. On the contrary, the dynamic on-demand dis-
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Free
Background
RECV
SEND
■ Figure 3. TDMA based slot reservation expanded with more nodes. tributed TDMA scheduling scheme, proposed in this article, selects the appropriate slots that minimize the end-to-end transmission for every path. Also, since the slot allocation takes place during the connection setup phase, the allocation may follow the changing requirements of multimedia traffic. Thus, the proposed strategy can allow more concurrent connections while minimizing the end-to-end delay.
DYNAMIC TDMA ALLOCATION The operation of the DDETSA is illustrated in Fig. 2 and Fig. 3. Figure 2 shows the sequence of operations when a connection is established at an initially idle ad hoc network. The rectangles represent the TDMA Frame reservations on each node in the transmission path. More specifically, the uncolored slots (free) are the unallocated slots, the green slots (SEND) are reserved for transmission at each node, the gray slots (RECV) are reserved for reception at each node, and the light gray slots (background) are reserved by neighboring nodes to ensure collision avoidance. Figure 3 shows how the slots have been allocated at every node, when a new connection is established. The connection from the top left to the bottom right is established initially. Afterwards, a new connection is established from the bottom left to the upper right.
PERFORMANCE EVALUATION In order to evaluate the efficiency of the DDETSA algorithm, it is compared with two other TDMA scheduling algorithms proposed in the literature, namely, MFA and HNN-GA [5, 8]. The differences between the proposed algorithm and the MFA and HNN-GA TDMA algorithms may be summarized as follows. The other TDMA algorithms produce a TDMA schedule that is static and it is recalculated only when the
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SIMULATION TOPOLOGY The efficiency of the DDETSA dynamic TDMA scheduling algorithm is compared to the MFA and HNN-GA algorithms. In order to perform the comparison, we apply the DDETSA algorithm on the network topologies (Fig. 4) that were first introduced in [5] and since then are being used for measuring the efficiency of such schemes. The reason for using these network topologies is that these have been used as test networks in order to evaluate all the other schemes, and thus they can be used for a direct comparison between the DDETSA algorithm and the MFA and HNN-GA algorithms.
PERFORMANCE METRICS The other TDMA scheduling algorithms try to minimize the total produced frame length and at the same time to maximize the total capacity and minimize the average access delay at each node. These performance metrics are appropriate for the other algorithms, since they were designed to statically assign at least one time slot for each node in the network. On the contrary, DDETSA takes into consideration the dynamic requirements and the endto-end QoS limitations of the traffic. Thus, it is
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shown that the proposed algorithm can find the end-to-end transmission paths that have significantly smaller delays (counted in timeslots) than the other schemes. Obviously, the feasible set of end-to-end paths is extremely large for the above network topologies, so we have randomly selected a number of end-to-end pairs for each network and calculated the end-to-end delay for the shortest (in terms of delay) path that connects the pair of nodes. Note that the end-to-end delay for each path of the proposed scheme depends on the amount of background reservations that have been made in the neighborhood of a single node. However, the congested scenario could not be examined, because the other relevant schemes have not been designed for providing guaranteed per-flow reservations. Thus, more than one connection would share the same timeslots in the other schemes, making the expected end-to-end delay unpredictable.
PERFORMANCE EVALUATION RESULTS As mentioned above, the previously proposed scheduling algorithms are centralized and they do not take into account the end-to-end delay. In order to evaluate the efficiency of DDETSA, the network topologies presented in [5] were used (Fig. 4) and their performance was compared with the HNN-GA [8] and MFA [5] algorithms. For these networks, we measured the end-to-end delay that is caused by the TDMA scheduling algorithms. The performance evaluation results may be summarized as given in Table 1, which contains the end-to-end delay caused by each algorithm for the connection shown with an arrow in Fig. 4. As shown from Table 1, considering topology (a), which consists of 15 nodes, the end-to-end delays measured in timeslots for the MFA, HNN-GA, and the DDETSA algorithms are 6, 10, and 3 time slots (TSs), respectively. Also, for the considered topology (b), which consists of 30 nodes, the delays are 10, 6, and 3 TSs, respectively. Finally, for topology (c), which consists of 40 nodes, the delays are 31, 23, and 3 TSs,
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respectively. We also generated a large number of random scenarios for the previously mentioned topologies. For every topology, we applied a random connection generator and created a set of unique source-destination pairs. Since all the nodes of the network have the same probability to be chosen, the choice of the source and destination nodes was random. Also, every source-destination pair was chosen only once. The random connection generator was used in order to ameliorate the inability of exhaustively measuring the end-to-end to delay of every possible connection. The same set of connections was applied on all three TDMA scheduling schemes (HNNGA, MFA, and DDETSA). The produced delay of each connection and each scheduling was measured. Note that the end-to-end delay for a connection depends on the routing algorithm that created the forwarding path. It also needs to be noted that in many cases the path with the shortest delay is not always the shortest path. On the contrary, the shortest delay is found on paths that subsequent forwarding nodes are assigned transmission slots that closely follow one-another. Thus, the end-toend delay for each connection was measured on the path with the shortest possible delay, and the distance versus number of hops used for the connection, according to the TDMA scheduling scheme. Finally, the results regarding the end-to-end delay of every connection in each topology are classified according to the distance and the average end-to-end delay for every distance (Fig. 5). The end-to-end delays produced by the HNN-GA and MFA schemes are almost equal. The distributed end-to-end TDMA scheduling algorithm showed, on the average, approximately half the delays of the other schemes. The proposed algorithm has a good performance in terms of delay (counted in TSs) compared with MFA and HNN-GA TDMA algorithms (Table 1). Considering also the results, as depicted in Fig. 5(a–c), we may notice a very good performance in terms of delay versus distance (counted in hops) of the proposed algorithms compared to MFA and HNN-GA. We may also notice that extending the use of MFA and HNN-GA to end-to-end QoS provisioning has almost the same behavior, which is
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■ Table 1. Comparison of the DDETSA algorithm with the HNN-GA and MFA ones. The delay is counted in time slots for the end-to-end communication.
considerably worse than the proposed algorithm. Another important issue is the dynamic and distributed nature of the proposed algorithm. More specifically, asalready mentioned, MFA and HNN-GA create the schedule considering only the topology without taking into account the application requirements in contradiction of the DDETSA algorithm. Thus, for end-to-end QoS provisioning for multimedia applications in ad hoc networks, the use of the DDETSA TDMA algorithm is preferable to the use of the existing TDMA algorithms.
CONCLUSIONS As ad hoc networks mature, a number of advantages of this technology are revealed, making them suitable for a variety of environments, including commercial, educational, and even home environments. No network planning is required when designing an ad hoc network. These networks are created on demand, as needed. Furthermore, there is no need for costly wired infrastructure, making network deployment fast, easy, and cost effective. In order to efficiently deliver multimedia traffic, the network itself should provide the adequate QoS to the users. If TDMA is used in multihop networks, appropriate TDMA scheduling is required. The TDMA scheduling schemes proposed in the literature suffer from a number of disadvantages that prevent TDMA to be applied on ad hoc networks: • Centralized implementation • Static slot assignment • Large end-to-end delay
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If we take into account the distributed and dynamic nature of the DDETSA algorithm, it is obvious that it is an excellent scheduling scheme for end-to-end QoS provisioning for multimedia applications in ad hoc networks.
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The performance evaluation in this article has shown the very good behavior of DDETSA compared with MFA and HNN-GA in terms of delay. If we take into account the distributed and dynamic nature of the DDETSA algorithm, it is obvious that it is an excellent scheduling scheme for end-to-end QoS provisioning for multimedia applications in ad hoc networks.
Department of Electrical and Computer Science Engineering. His research interests are in the areas of communication networks (wireless broadband networks, sensor/ad hoc networks, WLANs, and IP, MIP, and SONET networks), neural networks, grid technologies, and computer vision. He has participated in several projects funded by EU and National Agencies and has several publications in journals, books, and conference proceedings. He has served on the technical program committees of several conferences. He is a guest editor and reviewer for several journals.
REFERENCES
D IMITRIOS J. V ERGADOS (
[email protected]) was accepted to the National Technical University of Athens in 1998 and received his diploma in electrical and computer engineering in 2003. Since then he has been a Ph.D. candidate with the National Technical University of Athens, School of Electrical and Computer Engineering.
[1] S. Floyd et al., “Equation-Based Congestion Control for Unicast Applications,” Proc. ACM Sigcomm 2000. [2] M. Handley et al., “TCP Friendly Rate Control (TFRC): Protocol Specification,” RFC 3448, http://www.rfcarchive.org/getrfc.php?rfc=3448 [3] H.-K. Wu and P.-H. Chuang, “Dynamic QoS Allocation for Multimedia Ad hoc Wireless Networks,” Mobile Networks and Apps., vol. 6, 2001, pp. 377–84. [4] A. Ephremides and T. V. Truong, “Scheduling Broadcast in Multihop Radio Networks,” IEEE Trans. Commun., vol. 38, Apr. 1990, pp. 456–60. [5] G. Wang and N. Ansari, “Optimal Broadcast Scheduling in Packet Radio Networks Using Mean Field Annealing,” IEEE JSAC, vol. 15, no 2, Feb. 1997, pp. 250–60. [6] H. Shi and L. Wang, “A Hybrid Neural Network for Optimal TDMA Transmission Scheduling in Packet Radio Networks,” 2005 IEEE Int’l. Joint Conf. Neural Networks, vol. 5, Aug. 2005, pp. 3210–13. [7] J.-C. Chen et al., “A Novel Broadcast Scheduling Strategy Using Factor Graphs and Sum-Product Algorithm,” IEEE GLOBECOM ’04, vol. 6, Dec. 2004, pp. 4048–53. [8] S. Salcedo-Sanz, C. Busono-Calzon, and A. R. FigueiralVidal, “A Mixed Neural-Genetic Algorithm for the Broadcast Scheduling Problem,” IEEE Trans. Wireless Commun., vol. 2, no. 2, 2003, pp. 277–83. [9] D. D. Vergados, D. J. Vergados, and C. Douligeris, “A New Approach for TDMA Scheduling in Ad Hoc Networks,” 10th IFIP Int’l. Conf. Pers. Wireless Commun., Colmar, France, 2005, pp. 107–14.
BIOGRAPHIES DIMITRIOS D. VERGADOS [M] (
[email protected]) is a lecturer at the University of the Aegean, Department of Information and Communication Systems Engineering. He received a B.Sc. degree in physics from the University of Ioannina and a Ph.D. degree in integrated communication networks from the National Technical University of Athens,
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C HRISTOS D OULIGERIS [SM] (
[email protected]) received a Diploma in electrical engineering from the National Technical University of Athens in 1984 and M.S., M.Phil., and Ph.D. degrees from Columbia University in 1985, 1987, and 1990, respectively. He has held positions with the Department of Electrical and Computer Engineering at the University of Miami, where he reached the rank of associate professor and was the associate director for engineering of the Ocean Pollution Research Center. He is currently teaching at the Department of Informatics of the University of Piraeus, Greece. He has served on technical program committees of several conferences. His main technical interests lie in the areas of security and performance evaluation of high-speed networks, neurocomputing in networking, resource allocation in wireless networks and information management, and risk assessment and evaluation for emergency response operations. He is a guest editor and reviewer for several journals. SPYRIDON L. TOMBROS (
[email protected]) received his diploma in electrical engineering from the University of Patras and his Ph.D. degree from the National Technical University of Athens in 1992 and 1997, respectively. From 1993 to 1997 he worked as research associate at the National Technical University of Athens. In 1997, he joined 4Plus SA as a senior engineer and later as managing director, having leading role in the design of ATM and UMTS traffic simulator and analysis systems. Also, all these years he has been involved in many national and EU research programmes in the area of broadband and mobile networks. Today he is projects manager at APEX AG, Switzerland.
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