Robust Routing in Networks of Mobile Radio Nodes

Mobile radio communication networks in the operational theater exhibit volatile network topology with rapid connectivity changes due to node mobility and the harsh conditions in the battlefield environment. Reliable packet transport becomes a challenging task in view of the constant connectivity changes. In this paper we present a systematic approach for reliable packet routing in mobile networks. A class of topology models that is broad enough to capture the topology changes encountered in a mobile network is introduced. The optimal routing policy is specified in terms of the Directed Acyclic shortest path Routing Graph (DARG). Two algorithms for computing the DARG are proposed. One of the two algorithms is iterative and amendable to distributed implementation. The DARG provided shortest path routing in random connectivity networks in analogy to the shortest path tree in fixed connectivity networks

A performance comparison of the contiguous allocation strategies in 3D mesh connected multicomputers

The performance of contiguous allocation strategies can be significantly affected by the distribution of job execution times. In this paper, the performance of the existing contiguous allocation strategies for 3D mesh multicomputers is re-visited in the context of heavy-tailed distributions (e.g., a Bounded Pareto distribution). The strategies are evaluated and compared using simulation experiments for both First-Come-First-Served (FCFS) and Shortest-Service-Demand (SSD) scheduling strategies under a variety of system loads and system sizes. The results show that the performance of the allocation strategies degrades considerably when job execution times follow a heavy-tailed distribution. Moreover, SSD copes much better than FCFS scheduling strategy in the presence of heavy-tailed job execution times. The results also show that the strategies that depend on a list of allocated sub-meshes for both allocation and deallocation have lower allocation overhead and deliver good system performance in terms of average turnaround time and mean system utilization

MNCM: A Critical Node Matching Approach to Scheduling for Input Buffered Switches With No Speedup

In this paper, we use fluid model techniques to establish new results for the throughput of input-buffered switches. Dai and Prabhakar have shown that any maximal size matching algorithm with speedup of 2 achieves 100% throughput. We introduce the maximum node containing matching (MNCM), which is a new class of matching algorithms that achieve 100% throughput with no speedup. The only assumption on the arrival processes is they satisfy the strong law of large numbers (SLLN). The MNCM policies only need to include ports whose weight (backlog) are above a threshold in the matching rather than finding a matching with maximum total weight. This simplified requirement enables us to introduce a new matching algorithm, maximum first matching (MFM), with O(N(2.5)) complexity. We show that MFM is a low-complexity algorithm with good delay performance. We also provide a deterministic upper bound for the buffering requirement of a switch with an MNCM scheduler, when the ports incoming traffic are admissible and (sigma, rho) regulated

Joint routing, scheduling and power control for large interference wireless networks

We consider the problem of joint routing, scheduling and power control in multi-hop wireless networks. We use a linear relation between link capacity and signal to interference noise ratio in our formulation. In a previous work, using a duality approach, the optimal link scheduling and power control that minimizes the total average transmission power is found. We formulate this problem as a linear programming problem with exponential number of constraints. To cope with the exponential number of constraints, we propose an iterative algorithm based on the cutting plane method. The separation oracle for the cutting plane algorithm turns out to be an element-wise concave optimization problem that can be effectively solved using branch and bound algorithm. We extend the same method to find the optimal routing scheduling and power control. Simulation results show that this methodology is more efficient and scalable compare to the previously proposed algorithm

Joint routing, scheduling and power control for large interference wireless networks

We consider the problem of joint routing, scheduling and power control in multi-hop wireless networks. We use a linear relation between link capacity and signal to interference noise ratio in our formulation. In a previous work, using a duality approach, the optimal link scheduling and power control that minimizes the total average transmission power is found. We formulate this problem as a linear programming problem with exponential number of constraints. To cope with the exponential number of constraints, we propose an iterative algorithm based on the cutting plane method. The separation oracle for the cutting plane algorithm turns out to be an element-wise concave optimization problem that can be effectively solved using branch and bound algorithm. We extend the same method to find the optimal routing scheduling and power control. Simulation results show that this methodology is more efficient and scalable compare to the previously proposed algorithm

Differentiated traffic engineering for QoS provisioning

We introduce a new approach for QoS provisioning in packet networks based on the notion of differentiated traffic engineering (DTE). We consider a single AS network capable of source based multi-path routing. We do not require sophisticated queuing or per-class scheduling at individual routers; instead, if a link is used to forward QoS sensitive packets, we maintain its utilization below a threshold. As a consequence, DTE eliminates the need for per-flow (IntServ) or per-class (DiffServ) packet processing tasks such as traffic classification, queueing, shaping, policing and scheduling in the core and hence poses a lower burden on the network management unit. Conversely, DTE utilizes network bandwidth much more efficiently than simple over-provisioning. In this paper, we propose a complete architecture and an algorithmic structure for DTE. We show that our scheme can be formulated as a non-convex optimization problem, and we present an optimal solution framework based on simulated annealing. We present a simulation-based performance evaluation of DTE, and compare our scheme to existing (gradient projection) methods

The effect of a computer-assisted cognitive remediation on improving cognitive functions in patients with schizophrenia: A before-after study

Background: Cognitive impairment is a chronic and disabling manifestation of schizophrenia. Objectives: This before-after study was conducted to examine the effect of a short course computer-assisted cognitive remediation on improving cognitive functions of patients with schizophrenia. Materials and Methods: Twenty patients with schizophrenia were enrolled into the study. The intervention consisted of 10 onehour sessions held 2-3 times a week, using the Cogpack software that includes tasks to improve attention, memory, and executive function. The patients' cognitive functioning was assessed before and after the remediation, using tests in the CANTAB battery, including stop signal task (SST) and choice reaction time (CRT) to assess attention levels, pattern recognition memory (PRM) and Paired associate learning (PAL) to examine memory, and stocking of Cambridge (SOC) and intra-extra dimensional task (IED) to evaluate executive function. Results: IED and SOC revealed a statistically significant improvement in executive function after the intervention. PAL revealed a significantimprovementinmemory functioning inmostaspects after the intervention, whilePRMdid not. CRTshoweda significant improvement in some aspects of attention and concentration after the intervention, while SST did not. Conclusions: This before-after study revealed that a relatively short course of a computer-assisted cognitive remediation can be applied to improve several aspects of cognitive functioning in patients with schizophrenia. A randomized controlled trial is required to establish the effectiveness of the intervention. © 2016, Mazandaran University of Medical Sciences

Isolation of biosurfactant producing bacteria from oil reservoirs

Biosurfactants or surface-active compounds are produced by microoaganisms. These molecules reduce surface tension both aqueous solutions and hydrocarbon mixtures. In this study, isolation and identification of biosurfactant producing bacteria were assessed. The potential application of these bacteria in petroleum industry was investigated. Samples (crude oil) were collected from oil wells and 45 strains were isolated. To confirm the ability of isolates in biosurfactant production, haemolysis test, emulsification test and measurement of surface tension were conducted. We also evaluated the effect of different pH, salinity concentrations, and temperatures on biosurfactant production. Among importance features of the isolated strains, one of the strains (NO.4: Bacillus .sp) showed high salt tolerance and their successful production of biosurfactant in a vast pH and temperature domain and reduced surface tension to value below 40 mN/m. This strain is potential candidate for microbial enhanced oil recovery. The strain4 biosurfactant component was mainly glycolipid in nature