Self-managing energy-efficient multicast support in MANETs under end-to-end reliability constraints

Dynamic networks, e.g. Mobile Ad hoc NETworks (MANETs), call for self-healing routing protocols to tolerate topological changes imposed by node mobility. Moreover, emerging time-critical MANET applications such as disaster response and rescue, and battlefield operations, require support for real-time, reliable data streaming, while maintaining energy efficiency. However, most of the energy-efficient routing protocols rely on configuration parameters which need to be estimated and specified before the deployment phase. This paper proposes a self-managing, energy-efficient multicast routing suite based on the self-stabilization paradigm. This suite uses (i) WECM, a Waste Energy Cost Metric designed for energy-efficient route selection, (ii) SS-SPST-E, a Self-Stabilizing, Shortest-Path Spanning Tree protocol for Energy efficiency based on WECM to maintain an energy-efficient, self-healing routing structure, (iii) SS-SPST-Efc, an enhanced SS-SPST-E with fault containment to decrease stabilization latency, (iv) AMO, an Analytical Model for Optimization framework to reduce the energy overhead of the route maintenance mechanism, and (v) self-configuration mechanisms that observe, estimate and disseminate the optimization parameters.The WECM’s innovation is that it considers the overhearing energy wasted. The AMO framework considers the link state change rate, application data traffic intensity, application packet delivery requirements, and the stabilization latency. Numerical evaluations show that SS-SPST-E slightly increases the energy consumption when compared with non-adaptive energy-efficient protocols such as EWMA because of its mechanism to handle mobility. Simulation results show that SS-SPST-Efc achieves the maximum balance between the energy-reliability trade-off while conforming to the end-to-end packet delivery requirement with an accuracy between 80% and 100%. The energy-reliability balance, measured in terms of the packet delivery ratio (PDR) per millijoules of energy expended, is at least 24% and 27% higher in SS-SPST-E and SS-SPST-Efc, respectively, when compared to the MAODV and ODMRP protocols.     

Distributed workflow mapping algorithm for maximized reliability under end-to-end delay constraint

A distributed scientific workflow mapping algorithm for maximized reliability under certain end-to-end delay (EED) bound is proposed. It is studied in a heterogeneous distributed computing environment, where computing node and communication link failures are inevitable. The mapping decision and the stored table information is distributed among various nodes in order to achieve scalability and robustness, which are especially important for large-scale distributed systems. This Distributed Reliability Maximization workflow mapping algorithm under End-to-end Delay constraint (dis-DRMED) considers both the maximum reliability and the minimum EED objectives in a two-step procedure. In the first step, a mapping algorithm combining iterative Critical Path search and Layer-based priority assigning techniques (CPL) is adopted to minimize the EED by focusing on the optimal allocation of tasks on the critical path. In the second step, tasks on noncritical paths are remapped to improve the overall execution reliability. Simulation results under various system setups demonstrated that dis-DRMED achieved considerably higher reliability values under the same EED constraint compared with some representative workflow mapping algorithms.     

e-Transactions: end-to-end reliability for three-tier architectures

A three-tier application is organized as three layers: human users interact with front-end clients (e.g., browsers), middle-tier application servers (e.g., Web servers) contain the business logic of the application, and perform transactions against back-end databases. Although three-tier applications are becoming mainstream, they usually fail to provide sufficient reliability guarantees to the users. Usually, replication and transaction-processing techniques are applied to specific parts of the application, but their combination does not provide end-to-end reliability. The aim of this paper is to provide a precise specification of a desirable, yet realistic, end-to-end reliability contract in three-tier applications. The paper presents the specification in the form of the Exactly-Once Transaction (e-Transaction) abstraction: an abstraction that encompasses both safety and liveness properties in three-tier environments. It gives an example implementation of that abstraction and points out alternative implementations and tradeoffs     

Sequential optimization and reliability assessment for multidisciplinary design optimization under aleatory and epistemic uncertainties

In engineering design, to achieve high reliability and safety in complex and coupled systems (e.g., Multidisciplinary Systems), Reliability Based Multidisciplinary Design Optimization (RBMDO) has been received increasing attention. If there are sufficient data of uncertainties to construct the probability distribution of each input variable, the RBMDO can efficiently deal with the problem. However there are both Aleatory Uncertainty (AU) and Epistemic Uncertainty (EU) in most Multidisciplinary Systems (MS). In this situation, the results of the RBMDO will be unreliable or risky because there are insufficient data to precisely construct the probability distribution about EU due to time, money, etc. This paper proposes formulations of Mixed Variables (random and fuzzy variables) Multidisciplinary Design Optimization (MVMDO) and a method of MVMDO within the framework of Sequential Optimization and Reliability Assessment (MVMDO-SORA). The MVMDO overcomes difficulties caused by insufficient information for uncertainty. The proposed method enables designers to solve MDO problems in the presence of both AU and EU. Besides, the proposed method can efficiently reduce the computational demand. Examples are used to demonstrate the proposed formulations and the efficiency of MVMDO-SORA.     

Maintenance optimization in failure-prone systems under imperfect preventive maintenance

In the majority of the existing preventive optimization models only costs related to maintenance actions are accounted for, while breakdown and operational costs are usually ignored. Liao et al. (J Intell Manuf 21(6):875–884, 2010) proposed a preventive maintenance model to deal with this shortcoming. In the present paper, we revisit and discuss the results provided in Liao et al. (2010) and point out some inconsistencies in the maintenance optimization model proposed therein. Accordingly, we develop a new maintenance optimization model and discuss some of its main cost components. Furthermore, optimality conditions are also formally investigated and a solution method is provided. Numerical experiments are conducted to illustrate the validity of the proposed approach and results are compared with those provided in the original paper by Liao et al. (2010).     

Feature-based hybrid strategies for gradient descent optimization in end-to-end speech recognition

Multimedia Tools and Applications - With the increasing popularity of deep learning, deep learning architectures are being utilized in speech recognition. Deep learning based speech recognition...     

Multiperiod robust optimization for proactive resource provisioning in virtualized data centers

Energy management has become a significant concern in data centers for reducing operational costs. Using virtualization allows server consolidation, which increases server utilization and reduces energy consumption by turning off idle servers. This needs to consider the power state change overhead. In this paper, we investigate proactive resource provisioning in short-term planning for performance and energy management. To implement short-term planning based on workload prediction, this requires dealing with high fluctuations that are inaccurately predictable by using single value prediction. Unlike long-term planning, short-term planning can not depend on periodical patterns. Thus, we propose an adaptive range-based prediction algorithm instead of a single value. We implement and extensively evaluate the proposed range-based prediction algorithm with different days of real workload. Then, we exploit the range prediction for implementing proactive provisioning using robust optimization taking into consideration uncertainty of the demand. We formulate proactive VM provisioning as a multiperiod robust optimization problem. To evaluate the proposed approach, we use several experimental setups and different days of real workload. We use two metrics: energy savings and robustness for ranking the efficiency of different scenarios. Our approach mitigates undesirable changes in the power state of servers. This enhances servers’ availability for accommodating new VMs, its robustness against uncertainty in workload change, and its reliability against a system failure due to frequent power state changes.     

Efficient route optimization scheme for nested-NEMO

Network mobility (NEMO) basic support protocol maintains the connectivity when mobile router (MR) of a mobile network changes its point of attachment to the Internet by establishing a bi-directional tunnel between the MR and the home agent (HA). A packet from a correspondent node (CN) traverses through the tunnel to reach the mobile network. Nesting occurs in NEMO when a MR's new attachment point is in another mobile network that has also moved away from its home link. The level of tunneling increases as the level of nesting increases. Multiple levels of tunneling in nested NEMO adds multiple legs to a non-optimized routing path that the IP packets have to traverse in order to reach the final destination. As per our study, an efficient route optimization technique in NEMO, particularly in nested NEMO, is still a research challenge. In this paper, we propose an efficient route optimization scheme for nested NEMO. We use two care-of Addresses for each MR, as well as two types of entries, such as fixed and visiting, in the routing table in each MR. Our route optimization scheme removes the tunnels completely from the nested NEMO in a single step using only one binding update message irrespective of the number of levels in the nest. Our route optimization scheme also works for non-nested NEMO.     

Computer aided reliability for optimum maintenance planning

Computer aided Maintenance planning for mechanical equipment is presented in this work to implement the optimized extensive maintenance plan at a specific time horizon. The objective is to interchange the unscheduled corrective maintenance into scheduled preventive maintenance depending on historical data of equipment. This work is concerned with development of reliability analysis based on Weibull distribution. An optimization technique has been developed to provide the optimized preventive maintenance plan for the whole equipment during a required time horizon.     

Synthesis and optimization of the recovery route for residual products under uncertain product demand

The present work describes an optimization model for managing the recovery of residual products that originate at industrial plants. The framework for the proposed general network superstructure, where all possible process transformations, storage, transports and auxiliary operations are accounted for, is modeled using a maximal state task network representation. This framework is combined with the evaluation of a set of environmental impacts, quantified by metrics (for air, water pollution, etc.) through the minimum environment impact analysis methodology and is associated with waste generation at utility production and transportation levels. The final model is described as a mixed-integer linear programming model, which, once solved, is able to suggest the optimal processing and transport routes, while optimizing a given objective function and meeting design and environmental constraints. For each solution obtained, a stochastic flexibility index is computed, allowing for the drawing of trade-off curves for investment decision support.     

Intra domain route optimization for ubiquitous network

The main advantage of a wireless network is user mobility, which calls for efficient routing support at the network layer. An architecture combines hierarchical mobile IPv6 and network mobility for a network mobile and mobile nodes move in tandem and make a hierarchy in the wireless network to management of micro-mobility and seamless handoff. But the capability of the architecture for intra domain route optimization is impaired. So we propose functionality in domain nodes to enable intra domain path optimization for ubiquitous network. It is shown that intra domain cost effect is beneficial in every hierarchical domain that spans mesh network topology. We address the key function for our proposed scheme and analyze the usefulness of our proposed method using mathematically. We show that our proposed scheme performs much better than Network Mobility protocol, especially when the number of mobile nodes or mobile routers or correspondent nodes increases in hierarchically nested in ubiquitous networks.     

Network reliability optimization problem of interconnection network under node-edge failure model

The network reliability optimization problem for an interconnection network is to maximize the network reliability subjected to some constraints such as the total cost of the network. Even though, the problem is NP-Hard, many researchers have solved this problem in different ways but with a common assumption that nodes are perfect. But, this assumption is quite unrealistic in nature. In this paper, a new method based on artificial neural network is proposed to solve the network reliability optimization problem considering both the nodes and links of the interconnection networks to be imperfect. The problem is mapped onto an artificial neural network by constructing an energy function whose minimization process drives the neural network into one of its stable states. This stable state corresponds to a solution for the network reliability problem. Some existing methods are studied and compared with proposed method in evaluating the network reliability of some fully connected networks. The comparison reports the proposed method to be better than its counterparts in maximizing the network reliability. The proposed method is used to maximize the reliability of few fully connected networks subjected to some predefined total cost, where the node as well as the links of the networks may fail. Further, the behaviors of the cost as well as the time on the network reliability are discussed.     

A human reliability assessment of marine auxiliary machinery maintenance operations under ship PMS and maintenance 4.0 concepts

Cognition, Technology & Work - Maintenance is one of the core technical aspects on board ships, which is required for the ready availability, reliability, and efficiency of machinery equipment....     

Volunteer nodes of ant colony optimization routing for minimizing delay in peer to peer MANETs

A Mobile ad hoc Network (MANET) is an infrastructure less network that permits nodes to make a wireless network with mobility. In MANETs, the node linkages breaks are frequent due to all nodes are in movement. When neighbor nodes travel out of other node communication range connection among both mobile nodes breaks. Thus it makes delay and packet loss in the network. In the present Traffic Control method, several times, since the highest traffic, heavy rain, accidents, or other reasons, there may be probabilities of jam on roads. Thus, people could get delay owing to the highest traffic. Therefore, it is highly preferred to have an effective way to track the traffic on roads and thus select the suitable road that is traffic free. To resolve these problems, the volunteer Nodes of Ant Colony Optimization Routing (VNACO) is proposed. The primary objective of VNACO is to reduce both the delay and routing overhead in Peer to Peer (P2P) MANETs. Here, peer node act as a volunteer node and mobile node for transmitting data from source to destination. During data transmission, the relay node moving out of communication range when the volunteer node overheard the dropped data packet then deliver the data to the corresponding relay node. As a result, minimizes both the delay and packet losses. In VNACO, the volunteer’s nodes are elected based on node aptitude. Node aptitude is calculated by iterating node connectivity, transmission processing time, node energy and available bandwidth. In addition, an ant colony optimization algorithm to finds the optimal route and reduce the routing overhead in P2P MANETs. The significant application of this mechanism is utilized for the traffic management system. Network simulation results indicate that the VNACO mechanism is minimizing 22% delay and reducing 14% packet losses compared to the baseline protocol.

     

Improved cuckoo search for reliability optimization problems

An efficient approach to solve engineering optimization problems is the cuckoo search algorithm. It is a recently developed meta-heuristic optimization algorithm. Normally, the parameters of the cuckoo search are kept constant. This may result in decreasing the efficiency of the algorithm. To cope with this issue, the cuckoo search parameters should be tuned properly. In this paper, an improved cuckoo search algorithm, enhancing the accuracy and convergence rate of the cuckoo search algorithm, is presented. Then, the performance of the proposed algorithm is tested on some complex engineering optimization problems. They are four well-known reliability optimization problems, a large-scale reliability optimization problem as well as a complex system, which is a 15-unit system reliability optimization problem. Finally, the results are compared with those given by several well-known methods. Simulation results demonstrate the effectiveness of the proposed algorithm.     

公共自行车调度路径优化算法

针对如何计算出每次派出的最佳运输车数和每辆运输车的最优路线的问题,提出了一种用于求解的数学模型,并提出了一种基于改进的混合智能水滴算法。提出了节约算子、启发式算子、最大最小调制机制、变邻域搜索的融合策略。实验证明:所提出的新算法可以求解所述问题,与其他一些算法相比,求解效率更高。     

改进的PMIPv6域内路由优化策略

代理移动IPv6移动节点发生域内切换时,存在着重建路由优化路径时延长、切换开销大的问题,为此,提出一种改进的代理移动IPv6域内路由优化方案.在移动节点即将发生域内切换时,由新接入的移动网关发起切换,减少了切换过程中本地移动锚点的参与,在移动节点接入新网络之前完成优化路径的建立.仿真实验结果表明,新方案在切换时延和切换开销方面的性能优于原有的代理移动IPv6域内路由优化方案.     

Intuitionistic fuzzy optimization technique for solving multi-objective reliability optimization problems in interval environment

In designing phase of systems, design parameters such as component reliabilities and cost are normally under uncertainties. This paper presents a methodology for solving the multi-objective reliability optimization model in which parameters are considered as imprecise in terms of triangular interval data. The uncertain multi-objective optimization model is converted into deterministic multi-objective model including left, center and right interval functions. A conflicting nature between the objectives is resolved with the help of intuitionistic fuzzy programming technique by considering linear as well as the nonlinear degree of membership and non-membership functions. The resultants max–min problem has been solved with particle swarm optimization (PSO) and compared their results with genetic algorithm (GA). Finally, a numerical instance is presented to show the performance of the proposed approach.     

Dynamic route maintenance for geographic forwarding in mobile ad hoc networks

Traditional route maintenance requires mobile nodes periodically exchange beacon messages with their neighbors in geographic forwarding algorithms. The interval at which these nodes broadcast their beacon messages is typically fixed. However, determining an appropriate value for this interval is challenging. A longer interval reduces the number of beacons needed, but may result in significant location errors. Conversely, a shorter interval guarantees more accurate location information, but induces heavier control overheads. Additionally, since a fixed value is assigned to the lifetime of each routing entry, the forwarding algorithm cannot adapt well to different mobility environments. Therefore, this paper presents a dynamic route maintenance algorithm (DRM) for beacon-based geographic routing. In the approach, the mobile nodes dynamically adjust their beacon intervals based on their speed of movement. Moreover, the routing information can be well managed using the mobility prediction. The simulation results show that DRM not only significantly decreased the routing overheads in a low mobility scenario but also guaranteed the high quality packet delivery in high mobility environments.