Joint Optimal Access Point Selection and Channel Assignment in Wireless Networks

In wireless cellular networks or in other networks with single-hop communication, the fundamental access control problem pertains to access point (AP) selection and channel allocation for each user. For users in the coverage area of one AP, this involves only channel allocation. However, users that belong in the intersection of coverage areas of more than one AP can select the appropriate AP to establish connection and implicitly affect the channel assignment procedure. We address the joint problem of AP selection and channel assignment with the objective to satisfy a given user load vector with the minimum number of channels. Our major finding is that the joint problem reduces to plain channel allocation in a cellular network that emerges from the original one after executing an iterative and provably convergent clique load balancing algorithm. For linear cellular networks, our approach leads to minimum number of required channels to serve a given load vector. For 2D cellular networks, the same approach leads to a heuristic algorithm with a suboptimal solution due to the fact that clique loads cannot be balanced. Numerical results demonstrate the performance benefits of our approach in terms of blocking probability in a dynamic scenario with time-varying number of connection requests. The presented approach constitutes the basis for addressing more composite resource allocation problems in different context.     

Efficient resource utilization through carrier grouping forhalf-duplex communication in GSM-based MEO mobile satellitenetworks

In the near future, existing terrestrial radio networks are envisioned to integrate with satellite systems in order to provide global coverage. In order to establish communication for both nonhand-held and hand-held user terminals, the radio link design must allow full- and half-duplex operation, respectively, where the latter is desirable when radiation power restrictions are imposed. In addition, due to user mobility and wireless channel volatility, sophisticated resource management is required, so as to enhance system capacity. However, a major inherent problem of the satellite link is propagation delay, which may lead to inefficient resource allocation and reduced spectral efficiency. We address the resource allocation problem that arises in the context of a medium-Earth-orbit (MEO) satellite system with half-duplex communication capabilities. MEO satellite systems are characterized by large propagation delays and large intrabeam delay variations, which are shown to result in resource consumption. We propose a channel classification scheme, in which the available carriers are partitioned into classes and each class is associated with a range of propagation delays to the satellite. The suggested infrastructure results in better channel utilization and reduced call blocking rate and can be implemented with low signaling load     

Network State Estimation and Prediction for Real-Time Traffic Management

Advanced Traveler Information Systems (ATIS) and Advanced Traffic Management Systems (ATMS) have the potential to contribute to the solution of the traffic congestion problem. DynaMIT is a real-time system that can be used to generate guidance for travelers. The main principle on which DynaMIT is based is that information should be consistent, and user optimal. Consistency implies that the traffic conditions experienced by the travelers are consistent with the condition assumed in generating the guidance. To generate consistent user optimal information, DynaMIT performs two main functions: state estimation and prediction. A demand simulator and a supply simulator interact to perform these tasks. A case study demonstrates the value of the system.     

Physical layer techniques and maximum throughput scheduling with antenna arrays

We consider the downlink of a wireless system, where a base station transmits to users with an antenna array. We introduce scheduling algorithms that employ randomization to achieve maximum throughput, at low computational complexity. The algorithms operate in conjunction with either one of two physical layer techniques, namely transmit beamforming and Costa precoding. Simulation results show that the proposed randomized scheduling with Costa precoding algorithms carry the superior performance of Costa precoding at the physical, over to throughput benefits at higher layers.     

SELFNET 5G mobile edge computing infrastructure: Design and prototyping

This paper presents the design and prototype implementation of the SELFNET fifth-generation (5G) mobile edge infrastructure. In line with the current and emerging 5G architectural principles, visions, and standards, the proposed infrastructure is established primarily based on a mobile edge computing paradigm. It leverages cloud computing, software-defined networking, and network function virtualization as core enabling technologies. Several technical solutions and options have been analyzed. As a result, a novel portable 5G infrastructure testbed has been prototyped to enable the preliminary testing of the integrated key technologies and to provide a realistic execution platform for further investigating and evaluating software-defined networking– and network function virtualization–based application scenarios in 5G networks.     

Re-Chord: A Self-stabilizing Chord Overlay Network

The Chord peer-to-peer system is considered, together with CAN, Tapestry and Pastry, as one of the pioneering works on peer-to-peer distributed hash tables (DHT) that inspired a large volume of papers and projects on DHTs as well as peer-to-peer systems in general. Chord, in particular, has been studied thoroughly, and many variants of Chord have been presented that optimize various criteria. Also, several implementations of Chord are available on various platforms. Though Chord is known to be very efficient and scalable and it can handle churn quite well, no protocol is known yet that guarantees that Chord is self-stabilizing, i.e., the Chord network can be recovered from any initial state in which the network is still weakly connected. This is not too surprising since it is known that the Chord network is not locally checkable for its current topology. We present a slight extension of the Chord network, called Re-Chord (reactive Chord), that turns out to be locally checkable, and we present a self-stabilizing distributed protocol for it that can recover the Re-Chord network from any initial state, in which the n peers are weakly connected. in O(nlogn) communication rounds. We also show that our protocol allows a new peer to join or an old peer to leave an already stable Re-Chord network so that within O((logn)²) communication rounds the Re-Chord network is stable again.     

Effect of carrageenan level and packaging during ripening on processing and quality characteristics of low-fat fermented sausages produced with olive oil

Eight low-fat fermented sausages were produced with partial replacement of pork backfat with olive oil. The total fat content of the sausages was 10% of which 8% was animal fat and 2% was olive oil. The sausages were produced with two types of carrageenan (ι- and κ-) in four levels (0%, 1%, 2% and 3%). ι-Carrageenan had a better effect (p<0.05) than κ-carrageenan on such characteristics as pH, weight loss and lipid oxidation of the sausages, as well as, on sensory attributes. Low-fat fermented sausages with κ-carrageenan had the same (p>0.05) firmness as high-fat commercial sausages (control). The carrageenan level of 3% negatively affected the firmness of the sausages. In a 2nd experiment, a high-fat control (30% total fat) and three low-fat fermented sausages (10% total fat) with olive oil were produced with three levels of ι-carrageenan (0%, 1% and 2%). Low-fat sausages were vacuum packed for the last two weeks of ripening. ι-Carrageenan added at levels up to 2% had a positive effect (p<0.05) on the physicochemical and microbiological characteristics of the low-fat fermented sausages. The application of vacuum packaging over last two weeks of ripening improved the physicochemical and microbiological characteristics of the sausages and resulted in sensory attributes equal to or better than the high-fat controls.     

Nonlinear Kalman Filtering Algorithms for On-Line Calibration of Dynamic Traffic Assignment Models

An online calibration approach that jointly estimates demand and supply parameters of dynamic traffic assignment (DTA) systems is presented and empirically validated through an extensive application. The problem can be formulated as a nonlinear state-space model. Because of its nonlinear nature, the resulting model cannot be solved by the Kalman filter, and therefore, nonlinear extensions need to be considered. The following three extensions to the Kalman filtering algorithm are presented: 1) the extended Kalman filter (EKF); 2) the limiting EKF (LimEKF); and 3) the unscented Kalman filter. The solution algorithms are applied to the on-line calibration of the state-of-the-art DynaMIT DTA model, and their use is demonstrated in a freeway network in Southampton, U.K. The LimEKF shows accuracy that is comparable to that of the best algorithm but with vastly superior computational performance. The robustness of the approach to varying weather conditions is demonstrated, and practical aspects are discussed.     

Optimal Transmission Rate Control Policies in a Wireless Link Under Partial State Information

We consider the problem of PHY layer transmission rate control for maximum throughput on a wireless link over a finite time horizon. For each link state there exists a most advantageous transmission rate for the controller. The controller needs to rely on incomplete link state information in the form of positive acknowledgements (ACKs) and negative acknowledgements (NACKs) for transmitted packets. We cast the problem as a partially observed Markov decision processes (POMDP). We focus on the special case of time-invariant or slowly time varying link quality with two states and two control options. In that case, the optimal control problem is a state estimation one and the optimal strategy is of threshold structure, where the thresholds are certain values of the belief of being in one of the two states. The policy admits a simple interpretation: increase rate when the number of successive ACKs exceeds a threshold, and decrease rate when the number of successive NACKs exceeds a threshold.