Integer Maximum Flow in Wireless Sensor Networks with Energy Constraint

A faster FPTAS for knapsack problem with cardinality constraint

The closest string and substring problems find applications in PCR primer design, genetic probe design, motif finding, and antisense drug design. For their importance, the two problems have been extensively studied recently in computational biology. Unfortunately both problems are NP-complete. Researchers have developed both fixed-parameter algorithms and approximation algorithms for the two problems. In terms of fixed-parameter, when the radius d is the parameter, the best-known fixed-parameter algorithm for closest string has time complexity O(ndd+1), which is still superpolynomial even if d = O(log n). In this paper we provide an O(n|Σ|O(d)) algorithm where Σ is the alphabet. This gives a polynomial time algorithm when d = O(log n) and Σ has constant size. Using the same technique, we additionally provide a more efficient subexponential time algorithm for the closest substring problem. In terms of approximation, both closest string and closest substring problems admit polynomial time approximation schemes (PTAS). The best known time complexity of the PTAS is O(nO(Ɛ-2 log 1/Ɛ)). In this paper we present a PTAS with time complexity O(nO(Ɛ-2)). At last, we prove that a restricted version of the closest substring has the same parameterized complexity as closest substring, answering an open question in the literature.

A tournament T = (V , A) is a directed graph in which there is exactly one arc between every pair of distinct vertices. Given a digraph on n vertices and an integer parameter k, the Feedback Arc Set problem asks whether the given digraph has a set of k arcs whose removal results in an acyclic digraph. The Feedback Arc Set problem restricted to tournaments is known as the k-Feedback Arc Set in Tournaments (k-FAST) problem. In this paper we obtain a linear vertex kernel for k-FAST. That is, we give a polynomial time algorithm which given an input instance T to k-FAST obtains an equivalent instance T ′ on O(k) vertices. In fact, given any fixed ϵ > 0, the kernelized instance has at most (2 + ϵ)k vertices. Our result improves the previous known bound of O(k2 ) on the kernel size for k-FAST. Our kernelization algorithm solves the problem on a subclass of tournaments in polynomial time and uses a known polynomial time approximation scheme for k- FAST.

#NFA refers to the problem of counting the words of length n accepted by a non-deterministic finite automaton. #NFA is #P-hard, and although fully-polynomial-time randomized approximation schemes (FPRAS) exist, they are all impractical. The first FPRAS for #NFA had a running time of Õ(n 17 m 17 ε -14 łog(δ -1 )), where m is the number of states in the automaton, δ ∈ (0,1] is the confidence parameter, and ε > 0 is the tolerance parameter (typically smaller than 1). The current best FPRAS achieved a significant improvement in the time complexity relative to the first FPRAS and obtained FPRAS with time complexity Õ((n 10 m 2 + n 6 m 3 )ε -4 łog 2 (δ -1 )). The complexity of the improved FPRAS is still too intimidating to attempt any practical implementation. In this paper, we pursue the quest for practical FPRAS for #NFA by presenting a new algorithm with a time complexity of O(n 2 m 3 łog(nm)ε -2 łog(δ -1 )). Observe that evaluating whether a word of length n is accepted by an NFA has a time complexity of O(nm 2 ). Therefore, our proposed FPRAS achieves sub-quadratic complexity with respect to membership checks.

Environmental conditions, energy, bandwidth, storage and processing constraints, application and wireless sensor network, especially in real-time usage faces serious challenges. Thus, providing methods for reliable data transmission at desirable rate which takes into consideration energy constraint is of great importance. In this paper, a routing metric is introduced for selection of intermediate nodes which transmit data between source and destination. This metric takes into account remaining energy of the node, buffer capacity, and transmission delay and link quality. It can be applied for directed diffusion. By analysis and simulation, we show its efficiency with respect to network lifetime, load balancing capability and end-to-end delay reduction.

Sampling-Based Approximation Schemes for Capacitated Stochastic Inventory Control Models

Pattern transformation-invariant schemes for wireless sensor networks based on an edge detection gradient-based mechanism

Wireless sensor networks are a collection of specially designed nodes to provide support to sensor information propagation. Sensor nodes are basically designed to sense data as sensor and distribute to servers for further analysis. Based on the specific requirements, the numbers of sensor nodes can range from hundreds to thousands. All the communication will take place through predefined network characteristics. WSNs generally face energy issues. LEACH is designed for efficient cluster formation. It provides an efficient energy solution for data transmission from node to base station. Various enhanced version of LEACH has been proposed by Assuming LEACH as base protocol. The energy constraints are a critical aspect in developing the routing protocols for WSNs. Designers and researchers have contributed their effort through enhancement in energy saving procedure into WSNs. In this work, the LEACH based protocols and their performance in WSN has been analysed. This research paper evaluates recent advancement in LEACH based approaches for Wireless Wide Area Sensor Network with comparison table.

Using wireless sensor networks (WSNs) in delay and reliability critical environments is highly desired due to their unique advantages such as low cost, ease of deployment, and redundancy. However, successful deployment of resource-limited WSNs in such applications requires strict quality-of-service (QoS) provisioning techniques to meet the desired latency and reliability targets of those applications. Implementation of QoS techniques in WSNs is significantly challenging since WSNs have been initially devised for low-data-rate non-real-time applications. Therefore, WSN designers and developers resort to different cross-layer interaction and optimization techniques to provision QoS in WSNs. In this paper, we present a survey on the state of the art of cross-layer QoS approaches in wireless terrestrial sensor networks to achieve delay and reliability bounds in critical applications. Our paper provides a unique classification of cross-layer QoS approaches in WSNs that allows surveying a large amount of studies with utmost clarity. Furthermore, we highlight the main challenges of implementing QoS protocols in WSNs and present an overview of QoS-aware WSN applications.

Multimedia delivery over Wireless Sensor Networks (WSNs) is energy critical. In this paper, we study an energy constrained cross layer optimization scheme to improve digital image quality in cross polarization discrimination (XPD) based Multiple Input Multiple Output (MIMO) WSNs. The contribution of this research can be summarized in three parts. First, link layer energy consumption and packet loss ratio in multirate XPD based MIMO WSN are modeled. Secondly, XPD based modulation optimization cross link and physical layer is proposed, achieving considerable energy efficiency. Finally, a new Position-Value (P- V) based Unequal Error Protection (UEP) scheme is studied and discussed in XPD MIMO WSNs, with more efficient resource allocation compared to traditional approaches. Simulation results show the proposed modulation optimization scheme improves energy efficiency considerably, and position based UEP achieves significant distortion-energy gain compared with traditional layer based resource allocation schemes in XPD MIMO WSNs.

A parametric characterization and an ε-approximation scheme for the minimization of a quasiconcave program

As a contention‐free channel access protocol, Time Division Multiple Access (TDMA) is widely applied in Energy Harvesting Wireless Sensor Networks (EH‐WSNs) due to ease of implementation. TDMA scheduling in EH‐WSNs faces the problem of low channel utilization since time slots assigned to some nodes may not be used by them due to shortage of energy or data. It is important to design TDMA scheduling schemes that enhance channel utilization. In this paper, the Fixed Frame Size Scheme (FFSS) and the Adaptive Frame Size Scheme (AFSS) are proposed to improve channel utilization of EH‐WSNs. The FFSS aims at the optimal TDMA slot assignment for the TDMA scheduling with fixed frame size, and the AFSS considers the TDMA with variable frame size and targets both the optimal frame size and the optimal slot assignment. The optimization problems maximizing channel utilization are formulated for the FFSS and the AFSS, respectively, which take the upcoming energy and data into account. The optimization problems are transformed into assignment‐like problems and solved by the Hungarian‐based algorithm in polynomial time. Simulation results indicate that the proposed FFSS and AFSS can considerably improve channel utilization in the EH‐WSNs compared with the existing TDMA scheduling schemes.

Wireless industrial sensor networks are wireless sensor networks which have been adapted to industrial applications. Most techniques for wireless sensor networks can be applied to wireless industrial sensor networks. However, for industrial applications of wireless industrial sensor networks, new requirements such as real-time, reliable delivery need to be considered. In this paper, we propose EARQ, which is a novel routing protocol for wireless industrial sensor networks. It provides real-time, reliable delivery of a packet, while considering energy awareness. In EARQ, a node estimates the energy cost, delay and reliability of a path to the sink node, based only on information from neighboring nodes. Then, it calculates the probability of selecting a path, using the estimates. When packet forwarding is required, it randomly selects the next node. A path with lower energy cost is likely to be selected, because the probability is inversely proportional to the energy cost to the sink node. To achieve real-time delivery, only paths that may deliver a packet in time are selected. To achieve reliability, it may send a redundant packet via an alternate path, but only if it is a source of a packet. Experimental results show that EARQ is suitable for industrial applications, due to its capability for energy efficient, real-time, reliable communications.

Wireless sensor and actuator networks (WSANs) are heterogeneous networks composed of many different nodes that can cooperatively sense the environment, determine an appropriate action to take, then change the environment’s state after acting on it. As a natural extension of wireless sensor networks (WSNs), WSANs inherit from them a variety of research challenges and bring forth many new ones. These challenges are related to dealing with imprecise and vague information, solving complicated optimization problems or collecting and processing data from multiple sources. Computational intelligence (CI) is an overarching term denoting a conglomerate of biologically and linguistically inspired techniques that provide robust solutions to NP-hard problems, reason in imprecise terms and yield high-quality yet computationally tractable approximate solutions to real-world problems. Many researchers have consequently turned to CI in hope of finding answers to a plethora of WSAN-related challenges. This paper reviews the application of several methodologies under the CI umbrella to the WSAN field. We describe and categorize existing works leaning on fuzzy systems , neural networks , evolutionary computation , swarm intelligence , learning systems , and their hybridizations to well-known or emerging WSAN problems along five major axes: 1) actuation; 2) communication; 3) sink mobility; 4) topology control; and 5) localization. The survey offers informative discussions to help reason through all the studies under consideration. Finally, we point to future research avenues by: 1) suggesting suitable CI techniques to specific problems; 2) borrowing concepts from WSNs that have yet to be applied to WSANs; or 3) describing the shortcomings of current methods in order to spark interest on the development of more refined models.

In the paper, we present a polynomial-time approximation scheme (PTAS) for the minimum k-path connected vertex cover (MkPCVC) problem , which can be used to solve security problems in wireless sensor networks (WSNs), under fixed k≥ 2. In contrast to previously known approximation schemes for MkPCVC problem, our approach does not need location data of the vertices, and it can be applied to growth-bounded graphs. For any e 1 >0, the algorithm returns a (1+e 1)-approximation MkPCVC. We have proved the correctness and performance of the algorithm and shown its runtime is r∙n O(f(r)), where f(r) is a polynomial function, r = O((1/e)∙ln(1/e)) and e is only dependent on k and e 1.