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Adaptive energy-aware routing framework in transmission cost constrained wireless sensor networks
Abstract
Existing routing protocols in wireless sensor networks (WSN) utilize either the shortest path routing reducing (or minimizing) the transmission costs for real-time, inelastic traffic, or the load balancing routing (e.g. potential based routing) prolonging (or maximizing) the networks life time. However, how to efficiently deal with the trade-off between network life time and the least delay requirements is still an open problem. In this paper, by formulating the shortest path routing and the least energy cost routing in wireless sensor networks as L1-norm and L2-norm optimization problems, we propose an adaptive energy aware routing framework, namely, a convexly combined L1- and L2-norm optimization, that subsume the shortest path and the potential based routing strategies as two extreme cases. The proposed routing framework can adaptively select optimal (sparse) routes for source destination pairs, that satisfy a certain (elastic) transmission cost requirement, as well as maintaining the maximum network life time. The extensive simulation results demonstrate the efficiency of our routing framework.
... In the course of searching next optimal relay node, a dynamic route rather than static route need to be figured out continuously so as to avoid jeopardising the hot transmission path which may result in disrupting the overall network. With the development of various applications of WSN, new routing approaches are attracting much attention in recent years [15][16][17][18][19]. In [15], the authors proposed a routing algorithm for WSNs that needs a periodic and event-driven approach, and is required to adapt to different circumstances that the sensors face. ...
... The authors follow a separate source and channel coding approach and slow that the overall network optimization problem can be naturally decomposed into a source coding subproblem at the application layer and a wireless power control subproblem at the physical layer. Besides, the authors in [19] focused on minimizing energy consumption and maximizing network lifetime for data relay in one-dimensional queue network. An energy saving via opportunistic routing algorithm is designed to ensure minimum power cost during data relay and protect the nodes with relatively low residual energy. ...
Efficient and reliable routing plays a key role in wireless sensor networks in which routing design with regard to network availability and node lifetime needs to be deliberately considered. When multi-hop relay transmission is frequently applied to reduce a source node’s energy consumption and improve network capacity, a key issue affecting the nodes’ participation in the transmission is the problem of suitably determining the next hop in order to prolong each node’s lifetime and to maintain the energy-balancing of the whole network. In this study, we propose an energy-aware routing scheme by taking the Cauchy operator, node’s residual energy and routing distance into account. Based on Cauchy inequation, we achieve a relationship between the routing distance and the energy usage in the routing. By fixing a relay selection parameter and then identifying the next hop appropriately, we obtain a balancing energy-aware routing algorithm. Numerical results are provided to verify the lifetime and equilibrium of the energy distribution by comparing with them with those of a traditional approach.
... Different solutions have been introduced to overcome it [15,17,18,33]. The authors in [45] proposes a general routing framework to control the expected delay for the message flow by using transmission delay and energy dissipation as tuning parameters. Initially they formulate both shortest path routing [4,36,39] and potential based energy-aware routing [12,31] as integer linear programming and quadratic programming problems, respectively. ...
Currently, IEEE 802.11 standard for ad-hoc wireless mode is inadequate for multi-hop network. Recent efforts for the advancement of 802.11 standards, such as 11e for QoS support and 11n for high data rates (> 100 Mbps), are still limited as they are dependent on the wired infrastructure backbone and single-hop wireless communication. One major challenge in quality-of-service (QoS) oriented routing in wireless ad-hoc networks is to find a route that satisfies multiple constraints including energy consumption minimization, delay, node failure and throughput maximization.
In this paper, we propose a novel Dynamic Energy Efficient Routing (DEER) protocol that guarantees message delivery, maximum network lifetime and message flow. DEER uses those specific nodes on the fly which has maximum residual energy above a defined energy level for relaying message from a source to a destination.
Our proposed approach has been evaluated using realistic channel model and it demonstrates improved session lifetime and efficient data flow compared to Probabilistic Energy Profile, Efficient Hop Count Routing, Dijkstra and Random/opportunistic algorithms. In addition, DEER can lend itself easily to battery-based sensor networks or energy-harvested based sensor networks.
... To support reliable data communication, they present a multihop routing protocol that allows both intra-and intercluster communications. In [5], the authors formulate the shortest path routing and the least energy cost routing in wireless sensor networks as L1-norm and L2-norm optimization problems to maintain the maximum network life time. In [6], the authors have proposed to measure the connectivity of sensor nodes and use this parameter for selection of cluster head for forwarding data to BS. ...
Wireless Sensor Networks(WSNs) have problem of energy starvation in their operations. This constraint demands that the topology of communicating nodes should be limited. One of the ways of restraining the communicating nodes is by creating a Connected Dominating Set(CDS) of nodes out of them. In this paper, an Optimized Region Based Efficient Data(AORED) routing protocol for WSNs has been proposed. CDS has been employed in AORED to create a virtual backbone of communicating nodes in the network. The empirical study involving extensive simulations show that the proposed routing protocol outperforms the legacy DEEC and SEP protocols. AORED has increased number of transmission rounds, increased number of clusterheads and reduced number of packets sent to the basestation as compared to DEEC and SEP protocols.
... The research to develop efficient shortest path 48 algorithms has produced a variety of them, whose efficiency 49 primarily depends on the computational performance. Never-50 theless, until now, there is not clear which algorithm has the 51 best performance to find the shortest path [3], [4]. For instance, 52 Ji-Xian and Fang-Ling [5] claim that improves Dijkstra's 53 algorithm (DA) by reducing the number of repeated operations 54 and finding the minimum path length intuitively. ...
In this paper, we present a routing algorithm useful in the realm of centralized range-based localization schemes. The proposed method is capable of estimating the distance between two non-neighboring sensors in multi-hop wireless sensor networks. Our method employs a global table search of sensor edges and recursive functions to find all possible paths between a source sensor and a destination sensor with the minimum number of hops. Using a distance matrix, the algorithm evaluates and averages all paths to estimate a measure of distance between both sensors. Our algorithm is then analyzed and compared with classical and novel approaches, and the results indicate that the proposed approach outperforms the other methods in distance estimate accuracy when used in random and uniform placement of nodes for large-scale wireless networks. Furthermore, the proposed methodology is suitable for the implementation in centralized localization schemes, such as multi-dimensional scaling, least squares, and maximum likelihood to mention a few.
In this paper, we propose a novel routing metric, namely biased delivery probability (BDP), for measuring the wireless node's capacity of forwarding data packet to the destination. BDP essentially assigns different weights to the multi-paths information associated with different hop counts. An theoretical theory is established to compute the weights for different scenarios. Using BDP routing metric, we design a prioritized random walk routing (PRR) protocol for multihop wireless network, which incorporates random network coding strategy, and can force the coded packet only randomly "walk" through the higher priority node set, instead of randomly encountered nodes. In such a way, it provides a loop-free random walk forwarding and guarantees the packets consequently go through the right "direction" step by step to the destination. Extensive simulation results show that the PRR protocol can dramatically improve the network performance over existing forwarding scheme, in terms of the throughputs, the end to end delay and the number of transmissions.
Many social networks, e.g., Slashdot and Twitter, can be represented as directed graphs (digraphs) with two types of links between entities: mutual (bi-directional) and one-way (uni-directional) connections. Social science theories reveal that mutual connections are more stable than one-way connections, and one-way connections exhibit various tendencies to become mutual connections. It is therefore important to take such tendencies into account when performing clustering of social networks with both mutual and one-way connections.
In this paper, we utilize the dyadic methods to analyze social networks, and develop a generalized mutuality tendency theory to capture the tendencies of those node pairs which tend to establish mutual connections more frequently than those occur by chance. Using these results, we develop a mutuality-tendency-aware spectral clustering algorithm to identify more stable clusters by maximizing the within-cluster mutuality tendency and minimizing the cross-cluster mutuality tendency. Extensive simulation results on synthetic datasets as well as real online social network datasets such as Slashdot, demonstrate that our proposed mutuality-tendency-aware spectral clustering algorithm extracts more stable social community structures than traditional spectral clustering methods.
We propose a novel routing framework called PWave that supports multi-source multi-sink anycast routing for wireless sensor networks. A distributed and scalable potential field estimation algorithm and a probabilistic forwarding scheme are proposed to ensure low overhead and high resilience to network dynamics. Key properties of this framework are proved through theoretical analysis and verified through simulations.Using network lifetime maximization problem as one example, we illustrated the power of this framework by showing a 2.7 to 8 times lifetime extension over Directed Diffusion and up to 5 times lifetime extension over the energy-aware multipath routing.
The dynamic and lossy nature of wireless communication poses major challenges to reliable, self-organizing multihop networks. These non-ideal characteristics are more problematic with the primitive, low-power radio transceivers found in sensor networks, and raise new issues that routing protocols must address. Link connectivity statistics should be captured dynamically through an efficient yet adaptive link estimator and routing decisions should exploit such connectivity statistics to achieve reliability. Link status and routing information must be maintained in a neighborhood table with constant space regardless of cell density. We study and evaluate link estimator, neighborhood table management, and reliable routing protocol techniques. We focus on a many-to-one, periodic data collection workload. We narrow the design space through evaluations on large-scale, high-level simulations to 50-node, in-depth empirical experiments. The most effective solution uses a simple time averaged EWMA estimator, frequency based table management, and cost-based routing.
We study routing algorithms on wireless networks that use only short paths, for minimizing latency, and achieve good load balance, for balancing the energy use. We consider the special case when all the nodes are located in a narrow strip with width at most √3/2 ≈ 0.86 times the communication radius. We present algorithms that achieve good performance in terms of both measures simultaneously. In particular, the routing path is at most four times the shortest path length and the maximum load on any node is at most three times that of the most load-balanced algorithm without path-length constraint. In addition, our routing algorithms make routing decisions by only local information and, as a consequence, are more adaptive to topology changes due to dynamic node insertions/deletions or due to mobility.
Various applications in wireless networks, such as routing and query processing, can be formulated as random walks on graphs. Many results have been obtained for such applications by utilizing the theory of random walks (or spectral graph theory), which is mostly developed for undirected graphs. However, this formalism neglects the fact that the underlying (wireless) networks in practice contain asymmetric links, which are best characterized by directed graphs (digraphs). Therefore, random walk on digraphs is a more appropriate model to consider for such networks. In this paper, by generalizing the random walk theory (or spectral graph theory) that has been primarily developed for undirected graphs to digraphs, we show how various transmission costs in wireless networks can be formulated in terms of hitting times and cover times of random walks on digraphs. Using these results, we develop a unified theoretical framework for estimating various transmission costs in wireless networks. Our framework can be applied to random walk query processing strategy and the three routing paradigms-best path routing, opportunistic routing, and stateless routing-to which nearly all existing routing protocols belong. Extensive simulations demonstrate that the proposed digraph-based analytical model can achieve more accurate transmission cost estimation over existing methods.
How should flows through a network be organized, so that the network responds sensibly to failures and overloads? The question is currently of considerable technological importance in connection with the development of computer and telecommunication networks, while in various other forms it has a long history in the fields of physics and economics. In all of these areas there is interest in how simple, local rules, often involving random actions, can produce coherent and purposeful behaviour at the macroscopic level. This paper describes some examples from these various fields, and indicates how analogies with fundamental concepts such as energy and price can provide powerful insights into the design of routing schemes for communication networks.
Convex optimization problems arise frequently in many different fields. A comprehensive introduction to the subject, this book shows in detail how such problems can be solved numerically with great efficiency. The focus is on recognizing convex optimization problems and then finding the most appropriate technique for solving them. The text contains many worked examples and homework exercises and will appeal to students, researchers and practitioners in fields such as engineering, computer science, mathematics, statistics, finance, and economics.
In this paper we extend and generalize the standard spectral graph theory (or random-walk theory) on undirected graphs to digraphs. In particular, we introduce and define a normalized digraph Laplacian (Diplacian for short) Γ for digraphs, and prove that (1) its Moore–Penrose pseudoinverse is the discrete Green’s function of the Diplacian matrix as an operator on digraphs, and (2) it is the normalized fundamental matrix of the Markov chain governing random walks on digraphs. Using these results, we derive a new formula for computing hitting and commute times in terms of the Moore–Penrose pseudoinverse of the Diplacian, or equivalently, the singular values and vectors of the Diplacian. Furthermore, we show that the Cheeger constant defined in [Chung 057.
Chung , [Chung 05] F. R. K. 2005. “Laplacians and the Cheeger Inequality for Directed Graphs”. Annals of Combinatorics, 9: 1–19. [CrossRef], [Web of Science ®]View all references] is intrinsically a quantity associated with undirected graphs. This motivates us to introduce a metric, the largest singular value of the skewed Laplacian ∇=(Γ−Γ T )/2, to quantify and measure the degree of asymmetry in a digraph. Using this measure, we establish several new results, such as a tighter bound than that in [Chung 057.
Chung , [Chung 05] F. R. K. 2005. “Laplacians and the Cheeger Inequality for Directed Graphs”. Annals of Combinatorics, 9: 1–19. [CrossRef], [Web of Science ®]View all references] on the Markov chain mixing rate, and a bound on the second-smallest singular value of Γ.
In this article we present an interpretation ofeffective resistance in electrical networks in terms of random walks on underlying graphs. Using this characterization we provide simple and elegant proofs for some known results in random walks and electrical networks. We also interpret the Reciprocity theorem of electrical networks in terms of traversals in random walks. The byproducts are (a) precise version of thetriangle inequality for effective resistances, and (b) an exact formula for the expectedone-way transit time between vertices.
Routing is a critical operation in networks. In the context of data and sensor networks, routing strategies such as shortest-path, multi-path and potential-based ("all-path") routing have been developed. Based on the connection between routing and flow optimization in a network, in this paper we develop a unifying theoretical framework by considering flow optimization with mixed (weighted) L1/L2-norms. We obtain a surprising result: as we vary the trade-off parameter, the routing graphs induced by the optimal flow solutions span from shortest-path to multi-path to all-path routing - this entire sequence of routing graphs is referred to as the routing continuum. Our theory subsumes the earlier results showing the shortest path and all-path routing can be obtained from L1 and L2 flow optimization, respectively. We also develop an efficient iterative algorithm for computing the entire routing continuum. Several generalizations are also considered, with applications to traffic engineering and wireless sensor networks.
In this paper we develop a unified theoretical framework for estimating various transmission costs of packet forwarding in wireless networks. Our framework can be applied to the three routing paradigms, best path routing, opportunistic routing, and stateless routing, to which nearly all existing routing protocols belong. We illustrate how packet forwarding under each paradigm can be modeled as random walks on directed graphs (digraphs). By generalizing the theory of random walks that has primarily been developed for undirected graphs to digraphs, we show how various transmission costs can be formulated in terms of hitting times and hitting costs of random walks on digraphs. As representative examples, we apply the theory to three specific routing protocols, one under each paradigm. Extensive simulations demonstrate that the proposed digraph based analytical model can achieve more accurate transmission cost estimation over existing methods.
The terrorist attacks on September 11, 2001 have drawn attention to the use of wireless technology in order to locate survivors of structural collapse. We propose to construct an ad hoc network of wireless smart badges in order to acquire information from trapped survivors. We investigate the energy efficient routing problem that arises in such a network and show that since smart badges have very limited power sources and very low data rates, which may be inadequate in an emergency situation, the solution of the routing problem requires new protocols. The problem is formulated as an anycast routing problem in which the objective is to maximize the time until the first battery drains-out. We present iterative algorithms for obtaining the optimal solution of the problem. Then, we derive an upper bound on the network lifetime for specific topologies and describe a polynomial algorithm for obtaining the optimal solution in such topologies. Finally, numerical results regarding the upper bound and the algorithms are presented.
In this paper we extend and generalize the standard random walk theory
(or spectral graph theory) on undirected graphs to digraphs. In
particular, we introduce and define a (normalized) digraph Laplacian
matrix, and prove that 1) its Moore-Penrose pseudo-inverse is the
(discrete) Green's function of the digraph Laplacian matrix (as an
operator on digraphs), and 2) it is the normalized fundamental matrix of
the Markov chain governing random walks on digraphs. Using these
results, we derive new formula for computing hitting and commute times
in terms of the Moore-Penrose pseudo-inverse of the digraph Laplacian,
or equivalently, the singular values and vectors of the digraph
Laplacian. Furthermore, we show that the Cheeger constant defined in [6]
is intrinsically a quantity associated with undirected graphs. This
motivates us to introduce a metric - the largest singular value of
Δ:=(tilde{\cal L}-tilde{\cal L}^T)/2 - to quantify and measure the
degree of asymmetry in a digraph. Using this measure, we establish
several new results, such as a tighter bound (than that of Fill's in [9]
and Chung's in [6]) on the Markov chain mixing rate, and a bound on the
second smallest singular value of tilde{\cal L}.
Unlike traditional wireless routing protocols which use a single fixed path, opportunistic routing explicitly takes advantage of the broadcast nature of wireless communications by using a set of forwarders to opportunistically perform packet forwarding. A key issue in the design of opportunistic routing protocols is the forwarder list selection problem. In this paper we establish a general theory for analyzing the forwarder list selection problem, and develop an optimal solution, the minimum transmission selection (MTS) algorithm, which minimizes the expected number of transmissions and it can be incorporated into existing opportunistic routing protocols to select optimal forwarder lists. Our theory and algorithm can also be generalized to optimize other routing objectives such as minimizing the ex- pected transmission time or energy consumption in opportunistic routing. Through extensive simulations, we demonstrate that in more than 90% cases the MTS algorithm outperforms the ETX forwarder selection scheme used in existing opportunistic routing protocols such as ExOR and MORE. Index Terms—Forwarder list, Wireless routing, Opportunistic routing, Dynamic programming
Influence diffusion and influence maximization in large-scale online social
networks (OSNs) have been extensively studied, because of their impacts on
enabling effective online viral marketing. Existing studies focus on social
networks with only friendship relations, whereas the foe or enemy relations
that commonly exist in many OSNs, e.g., Epinions and Slashdot, are completely
ignored. In this paper, we make the first attempt to investigate the influence
diffusion and influence maximization in OSNs with both friend and foe
relations, which are modeled using positive and negative edges on signed
networks. In particular, we extend the classic voter model to signed networks
and analyze the dynamics of influence diffusion of two opposite opinions. We
first provide systematic characterization of both short-term and long-term
dynamics of influence diffusion in this model, and illustrate that the steady
state behaviors of the dynamics depend on three types of graph structures,
which we refer to as balanced graphs, anti-balanced graphs, and strictly
unbalanced graphs. We then apply our results to solve the influence
maximization problem and develop efficient algorithms to select initial seeds
of one opinion that maximize either its short-term influence coverage or
long-term steady state influence coverage. Extensive simulation results on both
synthetic and real-world networks, such as Epinions and Slashdot, confirm our
theoretical analysis on influence diffusion dynamics, and demonstrate the
efficacy of our influence maximization algorithm over other heuristic
algorithms.
The recent interest in sensor networks has led to a number of routing schemes that use the limited resources available at sensor nodes more efficiently. These schemes typically try to find the minimum energy path to optimize energy usage at a node. In this paper we take the view that always using lowest energy paths may not be optimal from the point of view of network lifetime and long-term connectivity. To optimize these measures, we propose a new scheme called energy aware routing that uses sub-optimal paths occasionally to provide substantial gains. Simulation results are also presented that show increase in network lifetimes of up to 40% over comparable schemes like directed diffusion routing. Nodes also burn energy in a more equitable way across the network ensuring a more graceful degradation of service with time.
The overlay approach has been widely used by many service
providers for traffic engineering in large Internet backbones. In the
overlay approach, logical connections are set up between edge nodes to
form a full mesh virtual network on top of the physical topology. IP
routing is then run over the virtual network. Traffic engineering
objectives are achieved through carefully routing logical connections
over the physical links. Although the overlay approach has been
implemented in many operational networks, it has a number of well-known
scaling issues. This paper proposes a new approach, which we call the
integrated approach, to achieve traffic engineering without full-mesh
overlaying. In the integrated approach, IP routing runs natively over
the physical topology rather than over the virtual network. Traffic
engineering objectives are realized by setting appropriate link metrics
in IP routing protocols. We first illustrate our approach with a simple
network, then present a formal analysis of the integrated approach and a
method for deriving the appropriate link weights. Our analysis shows
that for any given set of optimal routes of the overlay approach with
respect to a set of traffic demands, the integrated approach can achieve
exactly the same result by reproducing them as shortest paths. We
further extend the result to a more generic one: for any arbitrary set
of routes, as long as they are not loopy, they can be converted to
shortest-paths with respect to some set of positive link weights. A
theoretical insight of our result is that the optimal routing (with
respect to any objective function) is always shortest path routing with
respect to some appropriate positive link weights
An ad-hoc network of wireless static nodes is considered as it
arises in a rapidly deployed, sensor-based, monitoring system.
Information is generated in certain nodes and needs to reach a set of
designated gateway nodes. Each node may adjust its power within a
certain range that determines the set of possible one hop away
neighbors. Traffic forwarding through multiple hops is employed when the
intended destination is not within immediate reach. The nodes have
limited initial amounts of energy that is consumed at different rates
depending on the power level and the intended receiver. We propose
algorithms to select the routes and the corresponding power levels such
that the time until the batteries of the nodes drain-out is maximized.
The algorithms are local and amenable to distributed implementation.
When there is a single power level, the problem is reduced to a maximum
flow problem with node capacities and the algorithms converge to the
optimal solution. When there are multiple power levels then the
achievable lifetime is close to the optimal (that is computed by linear
programming) most of the time. It turns out that in order to maximize
the lifetime, the traffic should be routed such that the energy
consumption is balanced among the nodes in proportion to their energy
reserves, instead of routing to minimize the absolute consumed power
A popular account of the connection between random walks and electric networks.