Performance analysis of IEEE 802.11 ad hoc networks in the presence of exposed terminals

The paper evaluates the performance effects of exposed terminals in IEEE 802.11 ad hoc networks in finite load conditions. It derives analytical models for the estimation of channel utilization and media access delay for IEEE 802.11 ad hoc networks in finite load conditions with and without exposed terminals. The simulation results show that the analytical estimated channel utilization and media access delay metrics are fairly accurate.     

Exergoeconomic analysis and evaluation of energy-conversion plants—I. A new general methodology

A new approach to the combination of exergetic and economic analysis (exergoeconomic analysis) for the investigation of energy-conversion processes is presented. This approach allows the monetary evaluation of costs caused by irreversibilities (exergy losses), as well as comparisons between these costs and the investment and operating costs for each component of a plant. The present analysis permits identification and evaluation of inefficiencies in an energy-conversion plant and of opportunities for improvement.     

The Gestational Effects of Maternal Bone Marker Molecules on Fetal Growth,Metabolism and Long-Term Metabolic Health: A Systematic Review

Fetal exposure in adverse environmental factors during intrauterine life can lead to various biological adjustments, affecting not only in utero development of the conceptus, but also its later metabolic and endocrine wellbeing. During human gestation, maternal bone turnover increases, as reflected by molecules involved in bone metabolism, such as vitamin D, osteocalcin, sclerostin, sRANKL, and osteoprotegerin; however, recent studies support their emerging role in endocrine functions and glucose homeostasis regulation. Herein, we sought to systematically review current knowledge on the effects of aforementioned maternal bone biomarkers during pregnancy on fetal intrauterine growth and metabolism, neonatal anthropometric measures at birth, as well as on future endocrine and metabolic wellbeing of the offspring. A growing body of literature converges on the view that maternal bone turnover is likely implicated in fetal growth, and at least to some extent, in neonatal and childhood body composition and metabolic wellbeing. Maternal sclerostin and sRANKL are positively linked with fetal abdominal circumference and subcutaneous fat deposition, contributing to greater birthweights. Vitamin D deficiency correlates with lower birthweights, while research is still needed on intrauterine fetal metabolism, as well as on vitamin D dosing supplementation during pregnancy, to diminish the risks of low birthweight or SGA neonates in high-risk populations.     

Exploiting IP‐layer traffic prediction analytics to allocate spectrum resources using swarm intelligence

Elastic optical networks emerge as a reliable backbone platform covering the next‐generation connectivity requirements. It consists of advanced enabling components that provide the ability for extensive configuration leading to performance improvement in many areas of interest. Higher layer analytics like data from IP traffic prediction can assist in the process of allocating resources at the optical layer. This way, light connections are established more efficiently while targeting specific performance goals. For that purpose, an algorithm is designed and evaluated that exploits traffic prediction of data transfers between nodes of an optical metro or backbone network. Next, it utilizes adaptive functionality based on particle swarm optimization to find paths with available spectrum resources. These resources can facilitate more efficiently the future traffic demand, since traffic prediction data are considered when finding the related paths. The innovative resource allocation method is evaluated using small and very large real topologies. It scales (in execution time and resource usage) according to node increase, executes in feasible time frames, and reduces transponder utilization resulting to increased energy efficiency.     

An Autonomic QoS-centric Architecture for Integrated Heterogeneous Wireless Networks

In this paper the problem of seamless mobility and proficient joint radio resource management over an all-IP internetworked wireless heterogeneous environment is addressed. Nodes’ autonomicity is envisioned as the enabler to devise a Quality of Service (QoS) aware architecture for supporting a variety of services, founded on a common utility based framework that provides enhanced flexibility in reflecting different access networks’ type of resources and diverse QoS prerequisites, under a unified QoS-aware resource allocation optimization problem. This allows a more in-depth intrinsic wireless network convergence, beyond All-IP, driven by QoS-oriented resource management. This vision is demonstrated and instantiated for integrated WLAN and cellular (both CDMA and OFDMA) networks, providing a viable path towards the evolution and realization of the future wireless networking paradigm. Initial numerical results demonstrate the effectiveness of the proposed architecture and reveal the benefits of such a service oriented paradigm against other existing access oriented autonomic designs.     

Cross-layer modeling of adaptive wireless links for QoS support in heterogeneous wired-wireless networks

Future wired-wireless multimedia networks require diverse quality-of-service (QoS) support. To this end, it is essential to rely on QoS metrics pertinent to wireless links. In this paper, we develop a cross-layer model for adaptive wireless links, which enables derivation of the desired QoS metrics analytically from the typical wireless parameters across the hardware-radio layer, the physical layer and the data link layer. We illustrate the advantages of our model: generality, simplicity, scalability and backward compatibility. Finally, we outline its applications to power control, TCP, UDP and bandwidth scheduling in wireless networks. The work by Q. Liu and G. B. Giannakis are prepared through collaborative participation in the Communications and Networks Consortium sponsored by the U.S. Army Research Laboratory under the Collaborative Technology Alliance Program, Cooperative Agreement DAAD19-01-2-0011. The U.S. Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation thereon. The work by S. Zhou is supported by UConn Research Foundation internal grant 445157. Qingwen Liu (S’04) received the B.S. degree in electrical engineering and information science in 2001, from the University of Science and Technology of China (USTC). He received the M.S. degree in electrical engineering in 2003, from the University of Minnesota (UMN). He currently pursues his Ph.D. degree in the Department of Electrical and Computer Engineering at the University of Minnesota (UMN). His research interests lie in the areas of communications, signal processing, and networking, with emphasis on cross-layer analysis and design, quality of service support for multimedia applications over wired-wireless networks, and resource allocation. Shengli Zhou (M’03) received the B.S. degree in 1995 and the M.Sc. degree in 1998, from the University of Science and Technology of China (USTC), both in electrical engineering and information science. He received his Ph.D. degree in electrical engineering from the University of Minnesota, 2002, and joined the Department of Electrical and Computer Engineering at the University of Connecticut, 2003. His research interests lie in the areas of communications and signal processing, including channel estimation and equalization, multi-user and multi-carrier communications, space time coding, adaptive modulation, and cross-layer designs. He serves as an associate editor for IEEE Transactions on Wireless Communications since Feb. 2005. G. B. Giannakis (Fellow’97) received his Diploma in Electrical Engineering from the National Technical University of Athens, Greece, 1981. From September 1982 to July 1986 he was with the University of Southern California (USC), where he received his MSc. in Electrical Engineering, 1983, MSc. in Mathematics, 1986, and Ph.D. in Electrical Engineering, 1986. After lecturing for one year at USC, he joined the University of Virginia in 1987, where he became a professor of Electrical Engineering in 1997. Since 1999 he has been a professor with the Department of Electrical and Computer Engineering at the University of Minnesota, where he now holds an ADC Chair in Wireless Telecommunications. His general interests span the areas of communications and signal processing, estimation and detection theory, time-series analysis, and system identification -- subjects on which he has published more than 200 journal papers, 350 conference papers and two edited books. Current research focuses on transmitter and receiver diversity techniques for single- and multi-user fading communication channels, complex-field and space-time coding, multicarrier, ultra-wide band wireless communication systems, cross-layer designs and sensor networks. G. B. Giannakis is the (co-) recipient of six paper awards from the IEEE Signal Processing (SP) and Communications Societies (1992, 1998, 2000, 2001, 2003, 2004). He also received the SP Society’s Technical Achievement Award in 2000. He served as Editor in Chief for the IEEE SP Letters, as Associate Editor for the IEEE Trans. on Signal Proc. and the IEEE SP Letters, as secretary of the SP Conference Board, as member of the SP Publications Board, as member and vice-chair of the Statistical Signal and Array Processing Technical Committee, as chair of the SP for Communications Technical Committee and as a member of the IEEE Fellows Election Committee. He has also served as a member of the IEEE-SP Society’s Board of Governors, the Editorial Board for the Proceedings of the IEEE and the steering committee of the IEEE Trans. on Wireless Communications.     

Still Alive: Extending Keep-Alive Intervals in P2P Overlay Networks

Detecting node failures within Peer-to-Peer networks is an inherent trade-off between timely detection and consuming bandwidth on network maintenance. In the absence of user-driven messages, the majority of P2P networks rely upon the exchange of periodic keep-alive messages to maintain connections and network topology. We investigate three novel algorithms which prioritise keep-alive messages to nodes that are more likely to have failed. In doing so, these algorithms significantly reduce the expected delay between failures occurring and their subsequent detection in comparison to the standard approach, whilst consuming similar levels of bandwidth. Our algorithms build upon several studies that have shown that older peers are more likely to remain in the network than their short-lived counterparts. Each of our algorithms increase the interval between successive keep-alive messages as peers age in the system, based upon the distribution of peer session times and the current age of peers. We extensively describe the details of each algorithm, before comparing them to the standard periodic approach using simulations based upon measured network data. Furthermore, we show that these algorithms are complimentary to existing gossip-based mechanisms and investigate alternate methods of ascertaining a node??s age so that our algorithms can be robustly deployed in untrustworthy environments.