A survey on energy-aware security mechanisms

The increasing adoption of mobile devices as the preferred tool to access the Internet imposes to deepen the investigation of security aspects. In parallel, their power constrained nature must be explicitly considered in order to analyze security in an effective and comprehensive manner. This aspect, which is often neglected in the literature, allows investigating two important behaviors of mobile devices: (i) evaluate if all the layers accounting for privacy and security can be re-engineered or optimized to save power, and (ii) understand the effectiveness of draining energy to conduct attacks.In this perspective, this paper surveys and highlights the most recent work on energy-awareness and security. Also, it summarizes the current state of the art on general techniques to save energy, as well as tools to perform measurements. The major contributions of this survey are, thus, a review of past work aimed at minimizing the energy footprint of security mechanisms, and the identification of promising research trends, such as detecting attacks via anomalous power consumption.     

Link weight assignment and loop-free routing table update for link state routing protocols in energy-aware internet

In order to lessen the greenhouse effects and diminish environmental pollution, reducing energy usage is important in designing next generation networks. Shutting down the network devices that carry light load and redirecting their traffic flows to other routes is the most common way to reduce network energy consumption. Since traffic demands among node pairs vary in different time periods, an energy efficient network has to dynamically determine the optimal active links to adapt itself to network traffic changes. However, in current IP networks, shutting down and/or turning on links would trigger link state routing protocols to reconverge to a new topology. Since the convergence time would take tens of seconds, routing table inconsistencies among routers would result in network disconnection and even worse, generating traffic loops during the convergence interval. Removing routing images inconsistent among routers to prevent loops is a critical issue in energy efficient network and this issue is still not considered in the green network design yet. The contribution of the paper is presented in two parts. First, we propose a comprehensive approach to determine a network topology and a link metric for each time period. Traffic engineering is considered in our design such that flows going on the energy-aware network are within a predetermined percentage of the link capacity such that no congestion occurs in a statistical manner. Second, to avoid transient loops during time period changes, we propose a Distributed Loop-free Routing Update (DLRU) scheme to determine the correct sequence for updating the routing table. A scrupulous proof was also presented to ensure the loop-free property of the DLRU. In this paper, we formulate an integer linear programming to determine this multi-topology and link weight assignment problem. Due to its NP-hard property, we propose an efficient algorithm, termed Lagrangian Relaxation and Harmonic Series (LR&HS) heuristic. Numerical results demonstrate that the proposed LRHS approach outperforms the other approaches on several benchmark networks and random networks by providing up to 35%-50% additional energy saving in our experimental cases.     

Dynamic power management in energy-aware computer networks and data intensive computing systems

Energy awareness is an important aspect of modern network and computing system design and management, especially in the case of internet-scale networks and data intensive large scale distributed computing systems. The main challenge is to design and develop novel technologies, architectures and methods that allow us to reduce energy consumption in such infrastructures, which is also the main reason for reducing the total cost of running a network. Energy-aware network components as well as new control and optimization strategies may save the energy utilized by the whole system through adaptation of network capacity and resources to the actual traffic load and demands, while ensuring end-to-end quality of service. In this paper, we have designed and developed a two-level control framework for reducing power consumption in computer networks. The implementation of this framework provides the local control mechanisms that are implemented at the network device level and network-wide control strategies implemented at the central control level. We also developed network-wide optimization algorithms for calculating the power setting of energy consuming network components and energy-aware routing for the recommended network configuration. The utility and efficiency of our framework have been verified by simulation and by laboratory tests. The test cases were carried out on a number of synthetic as well as on real network topologies, giving encouraging results. Thus, we come up with well justified recommendations for energy-aware computer network design, to conclude the paper.     

Minimum–Maximum regret redundancy allocation with the choice of redundancy strategy and multiple choice of component type under uncertainty

This paper deals with a redundancy allocation problem in series–parallel systems with the choice of redundancy strategy, including active and cold standby strategies in which component’s time to failure follows an Erlang distribution. The scale parameter of Erlang distribution and consequently the reliability of each component are imprecise in terms of interval data, and only the lower and upper bounds are known. This problem, for the first time, is formulated through Min–Max regret criterion, which is commonly used to define robust solutions. The resulting problem formulation contains an unlimited number of constraints, and a Benders’ decomposition method is implemented to deal with the given problem. This method is compared with an enumeration method to show its effectiveness. The performance of the proposed model using the Benders’ decomposition method is examined over different problem sizes, and the associated results are analyzed.     

Efficient heuristics for energy-aware routing in networks with bundled links

Current networks are typically over-provisioned to ensure low delays, redundancy and reliability. These Quality of Service (QoS) guarantees are typically achieved using high end, high power network equipments. Their use, however, has led to concerns regarding green house gas emissions, which garnered a lot of attention recently and have resulted in a number of global initiatives aim at reducing the carbon footprint of Internet Service Providers (ISPs). These initiatives have motivated ISPs and researchers to design novel network algorithms and hardware that scale the usage or active time of a network according to traffic load. To this end, this paper considers the problem of shutting down a subset of bundled links during off-peak periods in order to minimize energy expenditure. Unfortunately, identifying the cables that minimize this objective is an NP-complete problem. Henceforth, we propose several practical heuristics based on Dijkstra’s algorithm and Yen’s k-shortest paths algorithm. We evaluated our heuristics on the Abilene network – with both real and synthetic traffic matrices and several larger random topologies with various loads. Our results show that the proposed heuristics to be effective and efficient. Moreover, our approaches could potentially reduce the energy usage of cables used in the Abilene network by up to 56.7%, assuming the traffic demands recorded on September 5, 2004.     

基于能量有效的逆向AODV路由协议研究

为了解决AODV协议在能耗性能上的不足,提高协议能量有效性,实现协议在多种网络环境中传输有效性与能量有效性的灵活折中,提出了一种改进的基于能量有效性的路由协议(energy-aware reverse AODV,ER-AODV).ER-AODV协议采用基于逆向AODV并结合最小功率以及能量均衡的设计方案,提出了一种改进的链路代价函数用来选择最佳传输路径.仿真结果表明,当代价函数中加权系数固定时,ER-AODV协议较AODV协议在能量有效性方面有着显著提高;当代价函数采用动态可调整的加权系数时,ER-AODV协议可以实现多种网络环境中传输有效性与能量有效性的灵活折中.     

端到端冗余流量消除技术的指纹选择算法研究

为了兼顾服务器端的内存消耗和有效性,在分析了现有端到端冗余流量消除技术中的指纹选择算法后,提出了贪婪指纹选择算法。该算法认为两个数据包中相同片段的邻接片段很有可能也是相同的,基于这一原理,邻接片段的指纹也将被选为代表指纹,有效地避免了在服务器端缓存整个数据包,大大减少了服务器端的内存消耗。仿真实验结果表明,该算法与现有的指纹选择算法相比,能够大大减少服务器端和用户终端的内存消耗,同时冗余消除率在10%-50%之间,与现有算法相近,证明了该算法的有效性。     

Radio planning of energy-aware cellular networks

This paper introduces a joint planning and management optimization approach for cellular networks to limit energy consumption while guaranteeing QoS and minimizing operators Capex and Opex. The modeling framework shows that an effective energy-efficient operation depends on the planning decisions. Conversely, it also shows that planning with energy management operation in view yields more versatile topologies than more traditional models based only on Capex. Results for LTE networks are provided and show that savings up to 65% in energy expenses are possible with slight increases in capital investments.     

The robust vehicle routing problem with time windows

This paper addresses the robust vehicle routing problem with time windows. We are motivated by a problem that arises in maritime transportation where delays are frequent and should be taken into account. Our model only allows routes that are feasible for all values of the travel times in a predetermined uncertainty polytope, which yields a robust optimization problem. We propose two new formulations for the robust problem, each based on a different robust approach. The first formulation extends the well-known resource inequalities formulation by employing adjustable robust optimization. We propose two techniques, which, using the structure of the problem, allow to reduce significantly the number of extreme points of the uncertainty polytope. The second formulation generalizes a path inequalities formulation to the uncertain context. The uncertainty appears implicitly in this formulation, so that we develop a new cutting plane technique for robust combinatorial optimization problems with complicated constraints. In particular, efficient separation procedures are discussed. We compare the two formulations on a test bed composed of maritime transportation instances. These results show that the solution times are similar for both formulations while being significantly faster than the solutions times of a layered formulation recently proposed for the problem.     

基于ARIMA-ANN预测模型的能量感知路由算法

针对传统能量感知OLSR协议在减少传输功率消耗和均衡节点剩余能量之间不能兼顾的特点,提出了一种新型的基于剩余能量比例和传输功率消耗的OLSR路由协议OLSR_RC,它利用上述两方面的指标构造复合能量开销,并将其作为路由选择的度量值。在减小网络开销的同时,也防止了部分低电量节点的能量被快速耗尽,延长了网络的生存周期。此外,新路由还采用ARIMA-ANN组合能量预测模型对节点的剩余电量进行预测,降低了由于拓扑控制(TC)消息丢失对选择路由所造成的影响。这种新型路由协议在无线传感器网络领域有比较广阔的应用前景。     

延迟容忍网络路由协议研究*

简介延迟容忍网络,论述和追踪国内外延迟容忍网络路由协议的研究进展,对现有的延迟容忍网络路由协议进行了分类研究,着重介绍了一些经典路由协议,对不同类别路由协议的特点和性能进行了分析和比较,并详细介绍了冗余副本消除,最后提出延迟容忍网络路由协议需要解决的问题和进一步的研究方向。     

Effective elimination of redundant association rules

It is well-recognized that the main factor that hinders the applications of Association Rules (ARs) is the huge number of ARs returned by the mining process. In this paper, we propose an effective solution that presents concise mining results by eliminating the redundancy in the set of ARs. We adopt the concept of δ tolerance to define the set of δ-Tolerance ARs (δ-TARs), which is a concise representation for the set of ARs. The notion of δ-tolerance is a relaxation on the closure defined on the support of frequent itemsets, thus allowing us to effectively prune the redundant ARs. We devise a set of inference rules, with which we prove that the set of δ-TARs is a non-redundant representation of ARs. In addition, we prove that the set of ARs that is derived from the δ-TARs by the inference rules is sound and complete. We also develop a compact tree structure called the δ-TAR tree, which facilitates the efficient generation of the δ-TARs and derivation of other ARs. Experimental results verify the efficiency of using the δ-TAR tree to generate the δ-TARs and to query the ARs. The set of δ-TARs is shown to be significantly smaller than the state-of-the-art concise representations of ARs. In addition, the approximation on the support and confidence of the ARs derived from the δ-TARs are highly accurate.     

一种基于能量感知的无线传感器网络混合路由协议

针对无线传感器网络的资源局限性、自组织性和网络拓扑结构的不确定性,提出了一种基于能量感知的平面路由和层次路由的混合路由协议。该协议可根据节点剩余能量的表现来判断节点的当前状态和路由选择,网络中各节点以"尽力而为"传输数据和"不得已"动态建立自适应簇头的方式进行网络通信。仿真结果比较表明:该协议具有较高簇头生成率和可靠的数据交付率,能更有效降低网络能量消耗。     

Energy-aware traffic engineering: A routing-based distributed solution for connection-oriented IP networks

The present paper deals with energy saving in IP networks and proposes a distributed energy-aware traffic engineering solution, named DAISIES, for switching off network links according to traffic variations. DAISIES works in a connection-oriented network, e.g. an IP/MPLS network, and follows a routing-based approach, i.e. it acts on the routing algorithm whilst link switch-off/on are consequence of routing decisions. The basic idea is to re-compute the path of each traffic demand when its requested capacity changes. A specific cost function is used to compute link weights into the shortest path routing algorithm with the goal of keeping unused as many links as possible. The main advantages of DAISIES can be summarized as follows: (i) no changes are required to current routing and signaling protocols, (ii) packet loss is completely avoided, (iii) both traffic decreasing and increasing and changing network conditions are automatically managed, and (iv) link switch-off/on take place transparently to the routing protocol and to other nodes. The performance of the proposed solution is evaluated in terms of energy saving relative to a static network optimized to support the peak traffic. Results show that DAISIES is able to save about 30% of energy in several traffic conditions. Moreover, it is shown that it is possible keeping the additional complexity low and still reaching high energy efficiency.     

资金需求不确定的银行卡网络鲁棒运作模型

研究了银行卡网络在实时高效运营的条件下,各成员银行的资金运作问题.在分析国内银联网络资金需求情况的基础上,运用随机模拟方法生成不确定需求情景,建立了以网络系统成本最小为目标的鲁棒模型.数值仿真结果表明,模型的解相对保守,能有效地保证银行卡网络运作的鲁棒性.     

Open vehicle routing problem with demand uncertainty and its robust strategies

We investigate the open vehicle routing problem with uncertain demands, where the vehicles do not necessarily return to their original locations after delivering goods to customers. We firstly describe the customer’s demand as specific bounded uncertainty sets with expected demand value and nominal value, and propose the robust optimization model that aim at minimizing transportation costs and unsatisfied demands in the specific bounded uncertainty sets. We propose four robust strategies to cope with the uncertain demand and an improved differential evolution algorithm (IDE) to solve the robust optimization model. Then we analyze the performance of four different robust strategies by considering the extra costs and unmet demand. Finally, the computational experiments indicate that the robust optimization greatly avoid unmet demand while incurring a small extra cost and the optimal return strategy is the best strategy by balancing the trade-off the cost and unmet demand among different robust strategies.     

基于SDN与NDN的卫星网络多约束路由算法

针对NDN卫星网络内容传输时延高、丢包率高且请求命中率低的问题,提出了一种基于SDN与NDN的卫星网络多约束路由算法,并命名为SNMcRA。基于SDN的集中控制与全局视图,通过建立多约束路由模型,将链路多约束信息与蚁群算法相结合以求解满足时延、带宽、丢包率多约束的代价最小路径,由节点在包转发的过程中动态完成转发表FIB和待定请求表PIT的构建。实验结果表明,该算法与DSP算法相比时延降低了35%,带宽利用率提升了29%,丢包率降低了17%,并且在请求命中率方面也具有显著优势。     

A cross-layer optimization based integrated routing and grooming algorithm for green multi-granularity transport networks

With the development of IP networks and intelligent optical switch networks, the backbone network tends to be a multi-granularity transport one. In a multi-granularity transport network (MTN), due to the rapid growth of various applications, the scale and complexity of network devices are significantly enhanced. Meanwhile, to deal with bursty IP traffic, the network devices need to provide continuous services along with excessive power consumption. It has attracted wide attention from both academic and industrial communities to build a power-efficient MTN. In this paper, we design an effective node structure for MTN. Considering the power savings on both IP and optical transport layers, we propose a mathematical model to achieve a cross-layer optimization objective for power-efficient MTN. Since this optimization problem is NP-hard (Hasan et al. (2010)  [11]) and heuristic or intelligent optimization algorithms have been successfully applied to solve such kinds of problems in many engineering domains (Huang et al. (2011)  [13], Li et al. (2011)  [17] and Dong et al. (2011)  [5]), a G  reen integrated R$R$outing and Grooming algorithm based on Biogeography-Based Optimization (Simon (2008)  [23]) (GRG_BBO) is also presented. The simulation results demonstrate that, compared with the other BBO based and state-of-the-art power saving approaches, GRG_BBO improves the power savings at a rate between 2%–15% whilst the high-level multi-user QoS (Quality of Services) satisfaction degree (MQSD) is guaranteed. GRG_BBO is therefore an effective technique to build a power-efficient MTN.     

能量感知的无线传感器网络多路径路由研究

针对现有多路径路由协议AOMDV的不足,提出了适用于无线传感器网络的能量感知多路径路由协议IMEA.IMEA在建立链路不相关的多路径时能优先建立节点不相关的多路径,在主路径失效时能优先选择与主路径共用节点最少的作为次优路径,而能量感知的路径选择策略能均衡网络中节点的能量消耗,实现数据传输路径的低能耗.对IMEA进行了仿真实验,结果表明IMEA有效延长了网络的生存时间.