This paper tackles the classical problem of transmission rate allocation in satellite networks where fading may negatively impact communications. Within the framework of multiobjective programming (MOP), this paper introduces a transmission rate allocation criterion among Earth stations (ESs) called L p -problem-based rate allocation (L p RA). The allocations provided by L p RA are representative of a compromise among the need of different performance metrics such as packet loss and transmission power (TP). This paper determines the condition for the existence and the value of a L p RA transmission rate allocation bound R bound , to which the transmission rate globally allocated by L p RA converges when the overall available transmission rate R TOT tends to infinity. The performance analysis, which is carried out through simulations under different satellite channel conditions, is aimed at investigating L p RA features, at showing the existence of the rate bound and the advantages concerning the rate allocation given by using L p RA, and at comparing L p RA with two other schemes in the literature concerning allocated rate, packet loss rate, transmit power, and execution time.

The main contribution of this chapter is the description of HySEP, Hybrid Simulated-Emulated Platform, developed by the authors and aimed at simulating/emulating heterogeneous networks to validate and test algorithms for traffic control and Quality of Service (QoS) assurance. Main features of HySEP are the appropriate level of accuracy and detail reached by using equipments available in most communication research laboratories, at low cost, and the easy configurability. HySEP is divided into three parts connected each others: the emulated core network; the simulated wireless access network communicating with the core network; and the real remote host. The overall platform is able to handle real traffic flows and overcomes the limitations introduced by other network simulators. HySEP is characterized by remarkable versatility and wide applicability to support the validation of different algorithms.

The availability of different access technologies enables the creation of heterogeneous networks supporting users mobility and assuring several different services. Meanwhile these networks require complex control techniques to assure Quality of Service (QoS) to users. Before implementing such networks, a deep performance analysis, through the use of network simulators or real models, is necessary. In particular the first ones (e.g. Network Simulator 3 - ns-3 among the others) are quite simple and easy to manage and configure, while the second ones assure the handling of real traffic flows.The main contribution of this paper is the description of an hybrid simulated and emulated network evaluation platform, developed by the authors. The platform purpose is to execute a performance analysis of different wireless networks such as Long Term Evolution (LTE) and Wi-Fi, connected to a core network implementing the Differentiated Service (DiffServ) protocol. The paper contains also the results of preliminary validation tests.

The diffusion of mobile devices, equipped by many different network interfaces, offers great benefits to mobile communications, in particular in the field of the so called Intelligent Transportation System (ITS). At the same time, the development of the IEEE 802.21 standard, that facilitates the interoperability between different access networks, assures further performance improvements. In this scenario, the network selection, that consists in determining the best Radio Access Network (RAN) among a set of available heterogeneous links, plays a fundamental role. The main contribution of this paper is a performance comparison among different network selection algorithms, within the framework proposed by the 802.21 standard. This performance comparison is obtained through a simulator developed by using Network Simulator 2 (ns-2).

This paper considers video transmissions through Smartphones in scenarios of emergency networks where satellite links are employed. Unfortunately, satellite channels may be affected by attenuation and fading, causing significant and frequent variations of the link quality. For this reason, static compression, coding and resource allocation are not optimal solutions to guarantee a satisfactory level of Quality of Experience: we propose to apply two techniques: i) a dynamic transmission rate allocation able to assign resources to the links according to their conditions; ii) an application layer joint coder for video transmission capable of adaptively compressing and protecting the transmitted video frames so recovering losses. The performance investigation of the proposal has been carried out through emulation and the obtained results are satisfactory and open the doors to future development of the proposal.

The network selection is a decisional process aimed at determining the Radio Access Network (RAN) that a Mobile Node (MN) has to use and represents the core-function of the Vertical Handover procedure. In this paper, the authors propose a new algorithm for the network selection, called Dynamic- Technique for Order of Preference by Similarity to Ideal So- lution (D-TOPSIS) that is a new formulation of the TOPSIS algorithm aimed at performing the same selection but requiring a minor number of operations and consequently reducing the time necessary to perform the selection. The main contribution of this work is the evaluation of the D-TOPSIS performance in a scenario where are available simultaneously a satellite network and Wi-Fi and WiMAX networks. The proposed approach is compared with other network selection methods found in the literature in two different cases: i) pedestrian, with a MN speed equal to 3 (m/s) and ii) vehicular, with a MN speed equal to 10 (m/s). The numerical results show that D-TOPSIS assures a good performance as well as a limited execution time in both cases.

Assuring a satisfactory level of Quality of Experience (QoE) to users is nowadays an important challenge for network service providers. At the same time, power consumption minimization is another important issue for network management. Consequently, the ideal goal is to maximize the QoE and, meanwhile, to minimize the power transmitted by network nodes. In telecommunications networks QoE is often linked to the transmission rate assured to a given application. Actually higher guaranteed transmission rate, lower packet loss, delay and jitter, which have a direct impact on QoE. In this view the requirement of maximizing QoE and minimizing power consumption conflict with each other because higher is the transmit rate better the QoE but higher required transmitted power. By taking the session time of a web navigation as a reference metric, in this paper, the authors propose a transmission rate allocation algorithm for satellite networks aimed at finding a satisfactory compromise between QoE and Transmitted Power (TP). Earth stations communicate with a satellite by using a common channel with an overall available transmission rate of R TOT . The allocation algorithm is formulated starting from the Multi Objective Programming theory and the L p -problem and it is called L p -problem based Rate Allocation (L p RA). Numerical results show that L p RA assures satisfying operative compromise between QoE improvement and power saving.

The Vertical Handover and the related Network Selection process play a fundamental role in supporting reliable communications over MANETs. The goal of the Network Selection is to determine the Radio Access Network (RAN) that a Mobile Node (MN) has to use among several available RANs. This decision process finds out the RAN that fits the MN requirements and has to provide the decision as rapidly as possible. A computationally heavy Network Selection algorithm can impact the whole handover process because it waits until the selection is carried out. This waste of time can have negative consequences in the quality of communications. The main contribution of this paper is the definition of a new Network Selection algorithm based on a different formulation of the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method found in the literature, called Dynamic-TOPSIS (D-TOPSIS). It is aimed at performing the same selection of the TOPSIS but with a significant reduction of necessary computational load. Finally, the numerical results highlight the execution time reduction obtained by applying the D-TOPSIS with respect to the standard algorithm, and other Network Selection techniques usually applied within Vertical Handover Processes.

The paper deals with the classical problem of the resource allocation in geostationary satellite scenarios where fading may negatively impact the communications. In more detail, we consider the case in which different performance metrics, such as Packet Loss and Power, are simultaneously taken into account. Starting from the wide literature in the field, this work tries to categorize the available and well-known resource allocation approaches into three groups: i) the capacity maximization with constrained power group, ii) the power minimization with constrained capacity group and iii) the multi-objective programming group. For each group a general mathematical formulation has been proposed and the main differences among the groups have been highlighted. The performance of the three listed groups are compared through simulations where two Earth Stations, afflicted by different fading conditions, have been considered. The comparison takes into account all the mentioned metrics (i.e., loss and power) and the computational complexity of the allocation approaches.

This paper introduces a criterion, based on theLpproblem, which has been employed to allocate capacity among Earth Stations. The obtained allocations permit a performance compromise between Packet Loss and Transmitted Power, which are taken into account as performance metrics. Moreover, starting from the proposedLp-problem based allocation and considering specific analytical models for the Packet Lo ss Probability (PLP) and the Transmitted Power (TP), the paper highlights the existence of a Capacity Bound, independent o f the overall capacity availableCTOT , on which the allocations converge. The main contribution of the paper concerns the performance analysis, carried out by simulation, which shows that the proposed method enables a significant savings of capacity and Transmitted Power and simultaneously, with only a limited worsening of the Packet Loss. Keywords-Satellite Communications; Multi-Objective Programming; Lp-problem based Allocation; Capacity Bound; Performance Analysis; I. I NTRODUCTION Resource allocation in modern satellite networks, such as satellite-sensor [1], LTE [2] and WiMax [3], plays a crucial role and needs to be deeply investigated. In several previou s works (such as [4], [5], [6] and [7]), we consider a scenario composed of a satellite communication system of Z earth stations that receive TCP traffic flows from a fixed number of sources and forward them onto a common geostationary satellite channel with an overall available capacity set eq ual to CTOT [bps]. The channel state is modeled by considering the fading effect, due to atmospheric conditions, that have a negative impact on the quality of communications. As a consequence, to compensate, we apply a Forward Error Correction (FEC) encoding system, selecting the code rate as a function of the fading level F , expressed in [dB], undergone by each station. From the viewpoint of the higher protocol layers (i.e., above the network layer) the redundancy bits added to protect the transmitted informati on cause a reduction of the available capacity for transmissio n. Taking into account the proposed scenario, the problem considered in this paper is the well known capacity allocation problem. The goal is to share the channel capacity among the earth stations according to the policy defined in [6] whose performance is further analysed and discussed in this paper . The proposed allocation problem models each transmission entity (i.e., the Earth Stations) using some functions, whi ch values are directly proportional to the capacity allocated , hat represent some metrics that need to be optimized simultaneously (e.g., the Packet Loss Probability, shortly PLP, an d the Transmitted Power, shortly TP, as done in this work). If the functions are in contrast to each other, as it happens in the case of this paper, the solution of the allocation problem must represent a compromise. For this reason we use the Multi-Objective Programming (MOP) framework to formulate the allocation problem thereby obtaining a solution also known as the Pareto Optimal Point (POP) set. To find out a single solution from this set, which is representative of the best compromise between the adopted metrics, we apply theLp-problem. An important consequence of the proposed approach is that its solution converges if CTOT increases (i.e., the Capacity Bound (CB) discussed in [6]). It enables a significant capacity savings with respect to the allocation of the overall resources available on the channel: CTOT . In fact, sharing all the channel capacity enables to optimize the value of a decreasing metric, however this is not true for an increasin g metric. So it is useless to allocate the whole capacity but a significant portion can be reserved to increase the number of earth stations that can transmit on the satellite channel . It is worth noticing that all the stations, that are allowed t o transmit, experience the same conditions in terms of PLP and TP. The aim of this paper is to present a performance analysis of the allocation problem proposed, by focusing on the evaluation of the benefits obtained, considering the value f the PLP and the TP, with respect to the allocation of the whole available capacityCTOT . Another key point of this paper is the evaluation of the increment of the number of earth stations computed by using a formula of the average number of earth stations, which can transmit with fixed value of PLP and TP, is presented. As next step of the research presented in this work, adaptive modulation and coding techniques, applied together with the resource allocation, for example based on the DVBS2 standard as in [8] and [9], will be object of thorough study. The rest of the paper is organized as follows. The next section presents a brief survey of the state of the art of resource allocation for satellite and wireless communicat ions systems. In Section II the model adopted for the capacity 7 Copyright (c) IARIA, 2013. ISBN: 978-1-61208-264-6 SPACOMM 2013 : The Fifth International Conference on Advances in Satellite and Space Communications

The task of a capacity allocation policy is to determine the optimal quantity of capacity that has to be shared among the transmitting entities. In this work the allocation problem is modelled by the Multi Objective Programming (MOP) theory. In particular, an allocation criterion based on the Lp-problem is proposed to find out a capacity allocation, among Earth Stations, representative of a compromise if Packet Loss Probability and Transmitted Power are taken into account as performance metrics. The paper also discusses the existence of a capacity allocation, called Capacity Bound, on which the performance converges independently of the overall capacity available CTOT. A performance analysis, carried out through simulations and under different satellite channel conditions, is finally proposed to investigate the allocation criterion performance and to show the Capacity Bound existence.

Lumbosacral radiculopathy is a very common pathology, frequently caused by degenerative spondyloarthropathies. However, radiculopathy may result from tumor in various locations within the spinal canal, more commonly extramedullary. Primary nerve root tumors are a rare cause of lumbosacral radiculopathy. The majority of primary spinal tumors are benign and slow growing, and their clinical manifestations may be difficult to distinguish from more common causes of radiculopathy, such as a disc herniation. To our knowledge, voluminous schwannomas with endoabdominal development have only rarely been observed. Lumbosacral radiculopathy is a common neurological syndrome which can be an important source of disability. Although the most common causes are disc herniation and chronic spinal arthropathy, physicians should be mindful of other causes, including neoplasms.