Hop Constrained Energy-Efficient Broadcasting: Insights from Massively Dense Ad Hoc Networks

We consider source-initiated broadcast session traffic in an ad hoc wireless network operating under a hard constraint on the end-to-end delay between the source and any node in the network. We measure the delay to a given node in the number of hops data travels from the source to that node, and our objective in this paper is to construct an energy-efficient broadcast tree that has a maximum depth Delta, where Delta; represents the end-to-end hop constraint in the network. We characterize the optimal solution to a closely related problem in massively dense networks using a dynamic programming formulation. We prove that the optimal solution can be obtained by an algorithm of polynomial time complexity O(Delta²). The solution to the dynamic program indicates that there is a single optimal policy applicable to all massively dense networks. Elaborating on the insights provided by the structure of the problem in massively dense networks, we design an algorithm for finding a solution to the hop constrained minimum power broadcasting problem in general networks. By extensive simulations, we demonstrate that our proposed optimization-based algorithm generates broadcast trees within 20% of optimality for general dense networks.     

Design and analysis of asynchronous wakeup for wireless sensor networks

In wireless sensor networks, scheduling the sleep duration of each node is one of the key elements for controlling critical performance metrics such as energy consumption and latency. Since the wakeup interval is a primary parameter for determining the sleeping schedule, how to tune the wakeup interval is crucial for the overall network performance. In this paper, we present an effective framework for tuning asynchronous wakeup intervals of IEEE 802.15.4 sensor networks from the energy consumption viewpoint. First, we derive an energy consumption model of each node as an explicit function of the wakeup interval, and empirically validate the derived model. Second, based on the proposed model, we formulate the problem of tuning the wakeup interval with the following two objectives: to minimize total energy consumption and to maximize network lifetime. We show that these two problems can be optimally solved by an iterative algorithm with global information by virtue of the convexity of the problem structure. Finally, as practical solutions, we further propose heuristic optimization algorithms that only exploit local information. In order to develop heuristic algorithms, we propose two broadcasting schemes, which are entitled as maximum wakeup interval broadcasting and efficient local maximum broadcasting. These broadcasting algorithms enable nodes in the network to have heterogeneous wakeup intervals.     

On the power efficiency of cooperative broadcast in dense wireless networks

A fundamental problem in large scale wireless networks is the energy efficient broadcast of source messages to the whole network. The energy consumption increases as the network size grows, and the optimization of broadcast efficiency becomes more important. In this paper, we study the optimal power allocation problem for cooperative broadcast in dense large-scale networks. In the considered cooperation protocol, a single source initiates the transmission and the rest of the nodes retransmit the source message if they have decoded it reliably. Each node is allocated an-orthogonal channel and the nodes improve their receive signal-to-noise ratio (SNR), hence the energy efficiency, by maximal-ratio combining the receptions of the same packet from different transmitters. We assume that the decoding of the source message is correct as long as the receive SNR exceeds a predetermined threshold. Under the optimal cooperative broadcasting, the transmission order (i.e., the schedule) and the transmission powers of the source and the relays are designed so that every node receives the source message reliably and the total power consumption is minimized. In general, finding the best scheduling in cooperative broadcast is known to be an NP-complete problem. In this paper, we show that the optimal scheduling problem can be solved for dense networks, which we approximate as a continuum of nodes. Under the continuum model, we derive the optimal scheduling and the optimal power density. Furthermore, we propose low-complexity, distributed and power efficient broadcasting schemes and compare their power consumptions with those-of-a traditional noncooperative multihop transmission     

Minimizing Broadcast Latency and Redundancy in Ad Hoc Networks

Network wide broadcasting is a fundamental operation in ad hoc networks. In broadcasting, a source node sends a message to all the other nodes in the network. In this paper, we consider the problem of collision-free broadcasting in ad hoc networks. Our objective is to minimize the latency and the number of transmissions in the broadcast. We show that minimum latency broadcasting is NP-complete for ad hoc networks. We also present a simple distributed collision-free broadcasting algorithm for broadcasting a message. For networks with bounded node transmission ranges, our algorithm simultaneously guarantees that the latency and the number of transmissions are within $O(1)$ times their respective optimal values. Our algorithm and analysis extend to the case when multiple messages are broadcast from multiple sources. Experimental studies indicate that our algorithms perform much better in practice than the analytical guarantees provided for the worst case.      

Minimum-Energy Broadcasting in Multi-hop Wireless Networks Using a Single Broadcast Tree

In this paper we address the minimum-energy broadcast problem in multi-hop wireless networks, so that all broadcast requests initiated by different source nodes take place on the same broadcast tree. Our approach differs from the most commonly used one where the determination of the broadcast tree depends on the source node, thus resulting in different tree construction processes for different source nodes. Using a single broadcast tree simplifies considerably the tree maintenance problem and allows scaling to larger networks. We first show that, using the same broadcast tree, the total power consumed for broadcasting from a given source node is at most twice the total power consumed for broadcasting from any other source node. We next develop a polynomial-time approximation algorithm for the construction of a single broadcast tree. The performance analysis of the algorithm indicates that the total power consumed for broadcasting from any source node is within 2H(n−1) from the optimal, where n is the number of nodes in the network and H(n) is the harmonic function. This approximation ratio is close to the best achievable bound in polynomial time. We also provide a useful relation between the minimum-energy broadcast problem and the minimum spanning tree, which shows that a minimum spanning tree may be a good candidate in sparsely connected networks. The performance of our algorithm is also evaluated numerically with simulations. A preliminary version of this work appeared in the Proceedings of WiOpt’04: Modeling and Optimization in Mobile, Ad hoc and Wireless Networks, University of Cambridge, UK, March 2004. Ioannis Papdimitriou was fully supported for this work by the Public Benefit Foundation “ALEXANDER S. ONASSIS”, Athens, Greece. Ioannis Papadimitriou was born in Veria, Greece, in 1976. He received his five year Diploma from the Department of Electronic and Computer Engineering, Technical University of Crete (Chania), Greece, in 1999 (graduating 2nd in class). He is currently a postgraduate student - Ph.D. candidate at the Telecommunications division, Department of Electrical and Computer Engineering, Aristotle University of Thessaloniki, Greece. His doctoral thesis deals with the design of wireless ad hoc networks. His research interests include broadcast and multicast communication, energy conservation, routing and topology control protocols, MAC layer and QoS issues. During his studies he has been honored with awards and scholarships by the Technical University of Crete, the Hellenic Telecommunications Organization S.A.(OTE S.A.) and Ericsson Hellas S.A. Mr. Papadimitriou has been a member of the Technical Chamber of Greece (TEE) since March 2000, and he has been supported by the Public Benefit Foundation ALEXANDER S. ONASSIS, Athens, Greece, with a scholarship for his doctoral studies from October 2001 to March 2005. Leonidas Georgiadis received the Diploma degree in electrical engineering from Aristotle University, Thessaloniki, Greece, in 1979, and his M.S. and Ph.D. degrees both in electrical engineering from the University of Connecticut, in 1981 and 1986, respectively. From 1981 to 1983 he was with the Greek army. From 1986 to 1987 he was Research Assistant Professor at the University of Virginia, Charlottesville. In 1987 he joined IBM T.J. Watson Research Center, Yorktown Heights, as a Research Staff Member. Since October 1995, he has been with the Telecommunications Department of Aristotle University, Thessaloniki, Greece. His interests are in the area of wireless networks, high speed networks, distributed systems, routing,scheduling, congestion control, modeling and performance analysis. Prof. Georgiadis is a senior member of IEEE Communications Society. In 1992 he received the IBM Outstanding Innovation Award for his work on goal-oriented workload management for multi-class systems.x     

Achieving energy‐neutral data transmission by adjusting transmission power for energy‐harvesting wireless sensor networks

Recently, benefiting from rapid development of energy harvesting technologies, the research trend of wireless sensor networks has shifted from the battery‐powered network to the one that can harvest energy from ambient environments. In such networks, a proper use of harvested energy poses plenty of challenges caused by numerous influence factors and complex application environments. Although numerous works have been based on the energy status of sensor nodes, no work refers to the issue of minimizing the overall data transmission cost by adjusting transmission power of nodes in energy‐harvesting wireless sensor networks. In this paper, we consider the optimization problem of deriving the energy‐neutral minimum cost paths between the source nodes and the sink node. By introducing the concept of energy‐neutral operation, we first propose a polynomial‐time optimal algorithm for finding the optimal path from a single source to the sink by adjusting the transmission powers. Based on the work earlier, another polynomial‐time algorithm is further proposed for finding the approximated optimal paths from multiple sources to the sink node. Also, we analyze the network capacity and present a near‐optimal algorithm based on the Ford–Fulkerson algorithm for approaching the maximum flow in the given network. We have validated our algorithms by various numerical results in terms of path capacity, least energy of nodes, energy ratio, and path cost. Simulation results show that the proposed algorithms achieve significant performance enhancements over existing schemes. Copyright © 2016 John Wiley & Sons, Ltd.     

Efficient broadcasting in multi-hop wireless networks with a realistic physical layer

Almost all existing broadcasting algorithms assume an ideal physical layer, in which a successful transmission is guaranteed if the distance between communicating nodes is less than a certain threshold, e.g., a transmission range. However, wireless communication links normally suffer from the characteristics of realistic physical layer, which significantly reduce the reliability of broadcasting among the nodes. This work addresses the minimal broadcasting problem in multi-hop wireless networks with a realistic physical layer. Given a probability p^*, the problem is to design a distributed broadcasting algorithm such that each node in the network receives the broadcasting packet with probability no less than p^* and the number of retransmissions is minimized. We show that this problem is NP-hard and propose a distributed greedy algorithm which maximizes the gain cost ratio at each node. We prove that the proposed algorithm guarantees that each node receives the broadcasting packet with probability no less than p^*, and analyze upper bound on the number of total retransmissions in the network. Simulation results show that our algorithm can provide near 100% coverage to the wireless network with a realistic physical layer, and reduce the number of retransmissions compared with modified traditional flooding schemes k-Flooding (pure flooding with multiple times) and ACK-Flooding (pure flooding with acknowledgement). We believe our algorithmic solution is efficient and practical for general existing multi-hop wireless networks.     

Fault-tolerant monitor placement for out-of-band wireless sensor network monitoring

Monitoring a sensor network to quickly detect faults is important for maintaining the health of the network. Out-of-band monitoring, i.e., deploying dedicated monitors and transmitting monitoring traffic using a separate channel, does not require instrumenting sensor nodes, and hence is flexible (can be added on top of any application) and energy conserving (not consuming resources of the sensor nodes). In this paper, we study fault-tolerant out-of-band monitoring for wireless sensor networks. Our goal is to place a minimum number of monitors in a sensor network so that all sensor nodes are monitored by k distinct monitors, and each monitor serves no more than w sensor nodes. We prove that this problem is NP-hard. For small-scale network, we formulate the problem as an Integer Linear Programming (ILP) problem, and obtain the optimal solution. For large-scale network, the ILP is not applicable, and we propose two algorithms to solve it. The first one is a ln(kn) approximation algorithm, where n is the number of sensor nodes. The second is a simple heuristic scheme that has much shorter running time. We evaluate our algorithms using extensive simulation. In small-scale networks, the latter two algorithms provide results close to the optimal solution from the ILP for relatively dense networks. In large-scale networks, the performance of these two algorithms are similar, and for relatively dense networks, the number of monitors required by both algorithms is close to a lower bound.     

One-to-All Broadcasting of Even Networks for One-Port and All-Port Models

Broadcasting is one of the most important communication primitives used in multiprocessor networks. In this letter, we demonstrate that the broadcasting algorithm proposed by Madabhushi and others is incorrect. We introduce efficient one-to-all broadcasting schemes of even networks for one-port and all-port models. The broadcasting time of the one-port model is 2d-3 and that of the all-port model is d-1. The total time steps taken by the proposed algorithms are optimal.     

Online Data Gathering for Maximizing Network Lifetime in Sensor Networks

Energy-constrained sensor networks have been deployed widely for monitoring and surveillance purposes. Data gathering in such networks is often a prevalent operation. Since sensors have significant power constraints (battery life), energy efficient methods must be employed for data gathering to prolong network lifetime. We consider an online data gathering problem in sensor networks, which is stated as follows: assume that there is a sequence of data gathering queries, which arrive one by one. To respond to each query as it arrives, the system builds a routing tree for it. Within the tree, the volume of the data transmitted by each internal node depends on not only the volume of sensed data by the node itself, but also the volume of data received from its children. The objective is to maximize the network lifetime without any knowledge of future query arrivals and generation rates. In other words, the objective is to maximize the number of data gathering queries answered until the first node in the network fails. For the problem of concern, in this paper, we first present a generic cost model of energy consumption for data gathering queries if a routing tree is used for the query evaluation. We then show the problem to be NP-complete and propose several heuristic algorithms for it. We finally conduct experiments by simulation to evaluate the performance of the proposed algorithms in terms of network lifetime delivered. The experimental results show that, among the proposed algorithms, one algorithm that takes into account both the residual energy and the volume of data at each sensor node significantly outperforms the others     

Game of energy consumption balancing in heterogeneous sensor networks

In a multi‐hop sensor network, sensors largely rely on other nodes as a traffic relay to communicate with targets that are not reachable by one hop. Depending on the topology and position of nodes, some sensors receive more relaying traffic and lose their energy faster. Such imbalanced energy consumption may lead to server problems like network partitioning. In this paper, we study the problem of energy consumption balancing (ECB) in heterogeneous sensor networks by assuming general any‐to‐any traffic pattern. We consider both factors of transmission power and forwarding load in measuring energy consumption. To find a solution, we formulate the problem as a strategic network formation game with a new utility function. We show that this game is guaranteed to converge to strongly connected topologies which have better ECB and bounded inefficiency. We propose a localized algorithm in which every node knows only about its k‐hop neighbourhood. Through simulations on uniform and clustered networks with various densities, we show that the performance of our algorithm is comparable with global and centralized algorithms. Copyright © 2015 John Wiley & Sons, Ltd.     

Localized broadcast incremental power protocol for wireless ad hoc networks

We investigate broadcasting and energy preservation in ad hoc networks. One of the best known algorithm, the Broadcast Incremental Power (BIP) protocol, constructs an efficient spanning tree rooted at a given node. It offers very good results in terms of energy savings, but its computation is centralized and it is a real problem in ad hoc networks. Distributed versions have been proposed, but they require a huge transmission overhead for information exchange. Other localized protocols have been proposed, but none of them has ever reached the performances of BIP. In this paper, we propose and analyze an incremental localized version of this protocol. In our method, the packet is sent from node to node based on local BIP trees computed by each node in the broadcasting chain. Local trees are constructed within the k-hop neighborhood of nodes, based on information provided by previous nodes, so that a global broadcasting structure is incrementally built as the message is being propagated through the network. Only the source node computes an initially empty tree to initiate the process. Discussion and results are provided where we argue that k = 2 is the best compromise for efficiency. We also discuss potential conflicts that can arise from the incremental process. We finally provide experimental results showing that this new protocol obtains very good results for low densities, and is almost as efficient as BIP for higher densities.     

Improved algorithms for computing with faulty SIMD hypercubes

Computation time for various primitive operations, such as broadcasting and global sum, can significantly increase when there are node failures in a hypercube. In this paper we develop nearly optimal algorithms for computing important basic problems on a faulty SIMD hypercube. In an SIMD hypercube, during a communication step, nodes can exchange information with their neighbors only across a specific dimension. Our parallel machine model is an n-dimensional SIMD hypercube Q _n with up to n-1 node faults. In an SIMD hypercube, during a communication step, nodes can exchange information with their neighbors only across a specific dimension. We use the concept of free dimension to develop our algorithms, where a free dimension is defined to be a dimension i such that at least one end node of any i-dimension link is nonfaulty. In an n-cube, with f < n faults, it is known that there exist n-f+1 free dimensions. Using free dimensions, we show that broadcasting and global sum can be performed in n+5 steps, thereby improving upon the previously known algorithms for these primitives. The broadcasting algorithms work independent of the location of source node and faulty nodes. This revised version was published online in June 2006 with corrections to the Cover Date.     

Localized energy efficient routing in mobile ad hoc networks

We consider the problem of localized energy aware routing in mobile ad hoc networks. In localized routing algorithms, each node forwards a message based on the position of itself, its neighbors and the destination. The objective of energy aware routing algorithms is to minimize the total power for routing a message from source to destination or to maximize the total number of routing tasks that a node can perform before its battery power depletes. In this paper we propose new localized energy aware routing algorithms called OLEAR. The algorithms have very high packet delivery rate with low packet forwarding and battery power consumption. In addition, they ensure good energy distribution among the nodes. Finally, packets reach the destination using smaller number of hops. All these properties make our algorithm suitable for routing in any energy constrained environment. We compare the performance of our algorithms with other existing energy and non‐energy aware localized algorithms. Simulation experiments show that our algorithms present comparable energy consumption and distribution to other energy aware algorithms and better packet delivery rate. Copyright © 2006 John Wiley & Sons, Ltd.     

Localized Construction of Low Weighted Structure and Its Applications in Wireless Ad Hoc Networks

We consider a wireless network composed of a set of n wireless nodes distributed in a two dimensional plane. The signal sent by every node can be received by all nodes within its transmission range, which is uniform and normalized to one unit. We present the first distributed method to construct a bounded degree planar connected structure LRNG, whose total link length is within a constant factor of the minimum spanning tree using total O(n) messages under the broadcast communication model. Moreover, in our method, every node only uses its two-hop information to construct such structure, i.e., it is localized method. We show that some two-hop information is necessary to construct any low-weighted structure. We also study the application of this structure in efficient broadcasting in wireless ad hoc networks. We prove that, for broadcasting, the relative neighborhood graph (RNG), which is the previously best-known sparse structure that can be constructed locally, could use energy O(n) times the total energy used by our structure LRNG. Our simulations show that the broadcasting based on LRNG consumes energy about 36% more than that by MST, and broadcasting based on RNG consumes energy about 64% more than that by MST. We also show that no localized method can construct a structure for broadcasting with total power consumption asymptotically better than LRNG. Xiang-Yang Li has been an Assistant Professor of Computer Science at the Illinois Institute of Technology since 2000. He hold MS (2000) and PhD (2001) degree at Computer Science from University of Illinois at Urbana-Champaign. He received his Bachelor degree at Computer Science and Bachelor degree at Business Management respectively from Tsinghua University, P.R. China in 1995. His research interests span the computational geometry, wireless ad hoc networks, game theory, optical networks, and cryptography. He is a Member of the ACM and IEEE.     

Minimum-Energy Broadcasting in Static Ad Hoc Wireless Networks

Energy conservation is a critical issue in ad hoc wireless networks for node and network life, as the nodes are powered by batteries only. One major approach for energy conservation is to route a communication session along the route which requires the lowest total energy consumption. This optimization problem is referred to as Minimum-Energy Routing. While the minimum-energy unicast routing problem can be solved in polynomial time by shortest-path algorithms, it remains open whether the minimum-energy broadcast routing problem can be solved in polynomial time, despite the NP-hardness of its general graph version. Recently three greedy heuristics were proposed in [11]: MST (minimum spanning tree), SPT (shortest-path tree), and BIP (broadcasting incremental power). They have been evaluated through simulations in [11], but little is known about their analytical performances. The main contribution of this paper is a quantitative characterization of their performances in terms of approximation ratios. By exploring geometric structures of Euclidean MSTs, we have been able to prove that the approximation ratio of MST is between 6 and 12, and the approximation ratio of BIP is between 13/3 and 12. On the other hand, we show that the approximation ratio of SPT is at least n/2, where n is the number of receiving nodes. To the best of our knowledge, these are the first analytical results for the minimum-energy broadcasting problem.     

Broadcasting in multi-radio multi-channel wireless networks using simplicial complexes

We consider the broadcasting problem in multi-radio multi-channel ad hoc networks. The objective is to minimize the total cost of the network-wide broadcast, where the cost can be of any form that is summable over all the transmissions (e.g., the transmission and reception energy, the price for accessing a specific channel). Our technical approach is based on a simplicial complex model that allows us to capture the broadcast nature of the wireless medium and the heterogeneity across radios and channels. Specifically, we show that broadcasting in multi-radio multi-channel ad hoc networks can be formulated as a minimum spanning problem in simplicial complexes. We establish the NP-completeness of the minimum spanning problem and propose two approximation algorithms with order-optimal performance guarantee. The first approximation algorithm converts the minimum spanning problem in simplical complexes to a minimum connected set cover (MCSC) problem. The second algorithm converts it to a node-weighted Steiner tree problem under the classic graph model. These two algorithms offer tradeoffs between performance and time-complexity. In a broader context, this work appears to be the first that studies the minimum spanning problem in simplicial complexes and weighted MCSC problem.     

Minimum-energy all-to-all multicasting in wireless ad hoc networks

A wireless ad hoc network consists of mobile nodes that are powered by batteries. The limited battery lifetime imposes a severe constraint on the network performance, energy conservation in such a network thus is of paramount importance, and energy efficient operations are critical to prolong the lifetime of the network. All-to-all multicasting is one fundamental operation in wireless ad hoc networks, in this paper we focus on the design of energy efficient routing algorithms for this operation. Specifically, we consider the following minimum-energy all-to-all multicasting problem. Given an all-to-all multicast session consisting of a set of terminal nodes in a wireless ad hoc network, where the transmission power of each node is either fixed or adjustable, assume that each terminal node has a message to share with each other, the problem is to build a shared multicast tree spanning all terminal nodes such that the total energy consumption of realizing the all-to-all multicast session by the tree is minimized. We first show that this problem is NP-Complete. We then devise approximation algorithms with guaranteed approximation ratios. We also provide a distributed implementation of the proposed algorithm. We finally conduct experiments by simulations to evaluate the performance of the proposed algorithm. The experimental results demonstrate that the proposed algorithm significantly outperforms all the other known algorithms.     

An exact algorithm for maximum lifetime data gathering tree without aggregation in wireless sensor networks

In wireless sensor networks, maximizing the lifetime of a data gathering tree without aggregation has been proved to be NP-complete. In this paper, we prove that, unless P = NP, no polynomial-time algorithm can approximate the problem with a factor strictly greater than 2/3. The result even holds in the special case where all sensors have the same initial energy. Existing works for the problem focus on approximation algorithms, but these algorithms only find sub-optimal spanning trees and none of them can guarantee to find an optimal tree. We propose the first non-trivial exact algorithm to find an optimal spanning tree. Due to the NP-hardness nature of the problem, this proposed algorithm runs in exponential time in the worst case, but the consumed time is much less than enumerating all spanning trees. This is done by several techniques for speeding up the search. Featured techniques include how to grow the initial spanning tree and how to divide the problem into subproblems. The algorithm can handle small networks and be used as a benchmark for evaluating approximation algorithms.

     

RPSF: A Routing Protocol with Selective Forwarding for Mobile Ad-Hoc Networks

Many existing reactive routing algorithms for mobile ad-hoc networks use a simple broadcasting mechanism for route discovery which can lead to a high redundancy of route-request messages, contention, and collision. Position-based routing algorithms address this problem but require every node to know the position and velocity of every other node at some point in time so that route requests can be propagated towards the destination without flooding the entire network. In a general ad-hoc network, each node maintaining the position information of every other node is expensive or impossible. In this paper, we propose a routing algorithm that addresses these drawbacks. Our algorithm, based on one-hop neighborhood information, allows each node to select a subset of its neighbors to forward route requests. This algorithm greatly reduces the number of route-request packets transmitted in the route-discovery process. We compare the performance of our algorithm with the well known Ad-hoc On-demand Distance Vector (AODV) routing algorithm. On average, our algorithm needs less than 12.6% of the routing-control packets needed by AODV. Simulation results also show that our algorithm has a higher packet-delivery ratio and lower average end-to-end delay than AODV.