Recover Fault Services via Complex Service-to-Node Mappings in Wireless Sensor Networks

With the motivation of seamlessly extending wireless sensor networks to the external environment, service-oriented architecture comes up as a promising solution. However, as sensor nodes are failure prone, this consequently renders the whole wireless sensor network to seriously faulty. When a particular node is faulty, the service on it should be migrated into those substitute sensor nodes that are in a normal status. Currently, two kinds of approaches exist to identify the substitute sensor nodes: the most common approach is to prepare redundancy nodes, though the involved tasks such as maintaining redundancy nodes, i.e., relocating the new node, lead to an extra burden on the wireless sensor networks. More recently, other approaches without using redundancy nodes are emerging, and they merely select the substitute nodes in a sensor node’s perspective i.e., migrating the service of faulty node to it’s nearest sensor node, though usually neglecting the requirements of the application level. Even a few work consider the need of the application level, they perform at packets granularity and don’t fit well at service granularity. In this paper, we aim to remove these limitations in the wireless sensor network with the service-oriented architecture. Instead of deploying redundancy nodes, the proposed mechanism replaces the faulty sensor node with consideration of the similarity on the application level, as well as on the sensor level. On the application level, we apply the Bloom Filter for its high efficiency and low space costs. While on the sensor level, we design an objective solution via the coefficient of a variation as an evaluation for choosing the substitute on the sensor level.     

<Emphasis Type="Italic">k</Emphasis>-Nearest neighbors tracking in wireless sensor networks with coverage holes

Target tracking is one of the important applications of wireless sensor networks (WSNs). Most of the existing approaches assume that the nodes are dense enough and ignore the coverage holes which are very common in WSNs because of random deployment of the sensor nodes, block of obstacles, etc. Besides, predicting the target’s location of the next time instance is unwise because of the quite a lot random factors. In this paper, we propose a novel target tracking approach without any predicting, called k-nearest neighbors tracking (k-NNT), to tackle the problems of energy efficiency, continuity and coverage holes. In k-NNT, only the k-nearest neighbors keep active and track the target when more than k nodes can sense the target; the k′-nearest neighbors work when there are only k′ nodes (k′ < k) can sense the target. A sophisticated rotation mechanism is designed to improve the continuity of the tracking process. In the worst case, none of the nodes can sense the target, i.e., the target enters into the coverage holes, and then k-NNT recovers by the Round Up mode (RU mode). The nodes on the perimeter of the coverage hole always keep active for a time threshold t and sense the around environment to find the target in time. Once a node finds the target, the RU mode is over and the irrelevant nodes turn into inactive mode. A series of simulation show that k-NNT performs superiorly compared with several existing approaches in terms of tracking accuracy, continuity and energy efficiency.     

A fault tolerant peer-to-peer spatial data structure

In recent years, many layered indexing techniques over distributed hash table (DHT)-based peer-to-peer (P2P) systems have been proposed to realize distributed range search. In this paper, we present a fault tolerant constant degree dynamic Distributed Spatial Data Structure called DSDS that supports orthogonal range search on a set of N d-dimensional points published on n nodes. We describe a total order binary relation algorithm to publish points among supernodes and determine supernode keys. A non-redundant rainbow skip graph is used to coordinate message passing among nodes. The worst case orthogonal range search cost in a d-dimensional DSDS with n nodes is \(O\left (\log n+m+\frac {K}{B}\right )\) messages, where m is the number of nodes intersecting the query, K is the number of points reported in range, and B is the number of points that can fit in one message. A complete backup copy of data points stored in other nodes provides redundancy for our DSDS. This redundancy permits answering a range search query in the case of failure of a single node. For single node failure, the DSDS routing system can be recovered to a fully functional state at a cost of O(log n) messages. Backup sets in DSDS nodes are used to first process a query in the most efficient dimension, and then used to process a query containing the data in a failed node in d-dimensional space. The DSDS search algorithm can process queries in d-dimensional space and still tolerate failure of one node. Search cost in the worst case with a failed node increases to \(O\left (d\log n+dm+\frac {K}{B}\right )\) messages for d dimensions.     

Sleeping on the Job: Energy-Efficient and Robust Broadcast for Radio Networks

We address the problem of minimizing power consumption when broadcasting a message from one node to all the other nodes in a radio network. To enable power savings for such a problem, we introduce a compelling new data streaming problem which we call the Bad Santa problem. Our results on this problem apply for any situation where: (1) a node can listen to a set of n nodes, out of which at least half are non-faulty and know the correct message; and (2) each of these n nodes sends according to some predetermined schedule which assigns each of them its own unique time slot. In this situation, we show that in order to receive the correct message with probability 1, it is necessary and sufficient for the listening node to listen to a \(\Theta(\sqrt{n})\) expected number of time slots. Moreover, if we allow for repetitions of transmissions so that each sending node sends the message O(log?^? n) times (i.e. in O(log?^? n) rounds each consisting of the n time slots), then listening to O(log?^? n) expected number of time slots suffices. We show that this is near optimal.We describe an application of our result to the popular grid model for a radio network. Each node in the network is located on a point in a two dimensional grid, and whenever a node sends a message m, all awake nodes within L _∞ distance r receive m. In this model, up to \(t<\frac{r}{2}(2r+1)\) nodes within any 2r+1 by 2r+1 square in the grid can suffer Byzantine faults. Moreover, we assume that the nodes that suffer Byzantine faults are chosen and controlled by an adversary that knows everything except for the random bits of each non-faulty node. This type of adversary models worst-case behavior due to malicious attacks on the network; mobile nodes moving around in the network; or static nodes losing power or ceasing to function. Let n=r(2r+1). We show how to solve the broadcast problem in this model with each node sending and receiving an expected \(O(n\log^{2}{|m|}+\sqrt{n}|m|)\) bits where |m| is the number of bits in m, and, after broadcasting a fingerprint of m, each node is awake only an expected \(O(\sqrt{n})\) time slots. Moreover, for t≤(1?ε)(r/2)(2r+1), for any constant ε>0, we can achieve an even better energy savings. In particular, if we allow each node to send O(log?^? n) times, we achieve reliable broadcast with each node sending O(nlog?²|m|+(log?^? n)|m|) bits and receiving an expected O(nlog?²|m|+(log?^? n)|m|) bits and, after broadcasting a fingerprint of m, each node is awake for only an expected O(log?^? n) time slots. Our results compare favorably with previous protocols that required each node to send Θ(|m|) bits, receive Θ(n|m|) bits and be awake for Θ(n) time slots.     

Near-optimal communication-time tradeoff in fault-tolerant computation of aggregate functions

This paper considers the problem of computing general commutative and associative aggregate functions (such as Sum) over distributed inputs held by nodes in a distributed system, while tolerating failures. Specifically, there are N nodes in the system, and the topology among them is modeled as a general undirected graph. Whenever a node sends a message, the message is received by all of its neighbors in the graph. Each node has an input, and the goal is for a special root node (e.g., the base station in wireless sensor networks or the gateway node in wireless ad hoc networks) to learn a certain commutative and associate aggregate of all these inputs. All nodes in the system except the root node may experience crash failures, with the total number of edges incidental to failed nodes being upper bounded by f. The timing model is synchronous where protocols proceed in rounds. Within such a context, we focus on the following question:

Under any given constraint on time complexity, what is the lowest communication complexity, in terms of the number of bits sent (i.e., locally broadcast) by each node, needed for computing general commutative and associate aggregate functions?

This work, for the first time, reduces the gap between the upper bound and the lower bound for the above question from polynomial to polylog. To achieve this reduction, we present significant improvements over both the existing upper bounds and the existing lower bounds on the problem.

     

On the Price of Heterogeneity in Parallel Systems

Suppose we have a parallel or distributed system whose nodes have limited capacities, such as processing speed, bandwidth, memory, or disk space. How does the performance of the system depend on the amount of heterogeneity of its capacity distribution? We propose a general framework to quantify the worst-case effect of increasing heterogeneity in models of parallel systems. Given a cost function g(C,W) representing the system’s performance as a function of its nodes’ capacities C and workload W (such as the makespan of an optimum schedule of jobs W on machines C), we say that g has price of heterogeneity α when for any workload, cost cannot increase by more than a factor α if node capacities become arbitrarily more heterogeneous. The price of heterogeneity also upper bounds the “value of parallelism”: the maximum benefit obtained by increasing parallelism at the expense of decreasing processor speed. We give constant or logarithmic bounds on the price of heterogeneity of several well-known job scheduling and graph degree/diameter problems, indicating that in many cases, increasing heterogeneity can never be much of a disadvantage.     

Diverse and proportional size-<Emphasis Type="Italic">l</Emphasis> object summaries using pairwise relevance

The abundance and ubiquity of graphs (e.g., online social networks such as Google\(+\) and Facebook; bibliographic graphs such as DBLP) necessitates the effective and efficient search over them. Given a set of keywords that can identify a data subject (DS), a recently proposed keyword search paradigm produces a set of object summaries (OSs) as results. An OS is a tree structure rooted at the DS node (i.e., a node containing the keywords) with surrounding nodes that summarize all data held on the graph about the DS. OS snippets, denoted as size-l OSs, have also been investigated. A size-l OS is a partial OS containing l nodes such that the summation of their importance scores results in the maximum possible total score. However, the set of nodes that maximize the total importance score may result in an uninformative size-l OSs, as very important nodes may be repeated in it, dominating other representative information. In view of this limitation, in this paper, we investigate the effective and efficient generation of two novel types of OS snippets, i.e., diverse and proportional size-l OSs, denoted as DSize-l and PSize-l OSs. Namely, besides the importance of each node, we also consider its pairwise relevance (similarity) to the other nodes in the OS and the snippet. We conduct an extensive evaluation on two real graphs (DBLP and Google\(+\)). We verify effectiveness by collecting user feedback, e.g., by asking DBLP authors (i.e., the DSs themselves) to evaluate our results. In addition, we verify the efficiency of our algorithms and evaluate the quality of the snippets that they produce.     

The weight-constrained maximum-density subtree problem and related problems in trees

Given a tree T=(V,E) of n nodes such that each node v is associated with a value-weight pair (val _v ,w _v ), where value val _v is a real number and weight w _v is a non-negative integer, the density of T is defined as \(\frac{\sum_{v\in V}{\mathit{val}}_{v}}{\sum_{v\in V}w_{v}}\). A subtree of T is a connected subgraph (V′,E′) of T, where V′?V and E′?E. Given two integers w _min? and w _max?, the weight-constrained maximum-density subtree problem on T is to find a maximum-density subtree T′=(V′,E′) satisfying w _min?≤∑_v∈V′ w _v ≤w _max?. In this paper, we first present an O(w _max? n)-time algorithm to find a weight-constrained maximum-density path in a tree T, and then present an O(w _max? ² n)-time algorithm to find a weight-constrained maximum-density subtree in T. Finally, given a node subset S?V, we also present an O(w _max? ² n)-time algorithm to find a weight-constrained maximum-density subtree in T which covers all the nodes in S.     

<Emphasis Type="Italic">i</Emphasis>SIM: An integrated design method for commercializing service innovation

Service innovation is focused on customer value creation. At its core, customer centric service innovation is technology-enabled, human-centered, and process-oriented. To profit from such innovation, firms need an integrated cross-disciplinary, holistic method to design and commercialize service innovation. From diverse but interrelated strands of theories from service science, strategic management, organization science and information systems literatures, this article develops a new integrated design method, known as iSIM (integrated Service Innovation Method), for simultaneous service innovation and business model design for sustained customer value co-creation with the firm. Following design science research method, the article theoretically defines and integrates iSIM’s seven constitutive design process-elements: service strategy, customer type / value proposition, service concept, service system, customer experience, service architecture and monetization into a coherent and end-to-end aligned integrated design method. It explains how iSIM would be holistically and iteratively practiced by practitioners, and conceptually exemplifies its utility via telco and Amazon case studies using secondary data. Perspectives on iSIM from selected practitioners are discussed which confirm iSIM’s potential utility for their business. Managerial implications of implementing the iSIM and potential areas for further research are also discussed.     

Barrier coverage of WSNs with the imperialist competitive algorithm

Barrier coverage in wireless sensor networks has been used in many applications such as intrusion detection and border surveillance. Barrier coverage is used to monitor the network borders to prevent intruders from penetrating the network. In these applications, it is critical to find optimal number of sensor nodes to prolong the network lifetime. Also, increasing the network lifetime is one of the important challenges in these networks. Various algorithms have been proposed to extend the network lifetime while guaranteeing barrier coverage requirements. In this paper, we use the imperialist competitive algorithm (ICA) for selecting sensor nodes to do barrier coverage monitoring operations called ICABC. The main objective of this work is to improve the network lifetime in a deployed network. To investigate the performance of ICABC, several simulations were conducted and the results of the experiments show that the ICABC significantly improves the performance than other state-of-art methods.     

Cost-Based Target Selection Techniques Towards Full Space Exploration and Coverage for USAR Applications in a Priori Unknown Environments

Full coverage and exploration of an environment is essential in robot rescue operations where victim identification is required. Three methods of target selection towards full exploration and coverage of an unknown space oriented for Urban Search and Rescue (USAR) applications have been developed. These are the Selection of the closest topological node, the Selection of the minimum cost topological node and the Selection of the minimum cost sub-graph. All methods employ a topological graph extracted from the Generalized Voronoi Diagram (GVD), in order to select the next best target during exploration. The first method utilizes a distance metric for determining the next best target whereas the Selection of the minimum cost topological node method assigns four different weights on the graph’s nodes, based on certain environmental attributes. The Selection of the minimum cost sub-graph uses a similar technique, but instead of single nodes, sets of graph nodes are examined. In addition, a modification of A* algorithm for biased path creation towards uncovered areas, aiming at a faster spatial coverage, is introduced. The proposed methods’ performance is verified by experiments conducted in two heterogeneous simulated environments. Finally, the results are compared with two common exploration methods.     

Strategies for utility maximization in social groups with preferential exploration

Social Group is group of interconnected nodes interested in obtaining common content (Scott, in Social network analysis, 2012). Social groups are observed in many networks for example, cellular network assisted Device-to-Device network (Fodor et al., in IEEE Commun Mag 50:170–177, 2012, Lei et al., in Wirel Commun 19:96–104, 2012), hybrid Peer-to-Peer content distribution (Christos Gkantsidis and Miller, in 5th International Workshop on Peer-to-Peer Systems, 2006, Vakali and Pallis, in IEEE Internet Comput 7:68–74, 2003) etc. In this paper, we consider a “Social Group” of networked nodes, seeking a “universe” of data segments for maximizing their individual utilities. Each node in social group has a subset of the universe, and access to an expensive link for downloading data. Nodes can also acquire the universe by exchanging copies of data segments among themselves, at low cost, using inter-node links. While exchanges over inter-node links ensure minimum or negligible cost, some nodes in the group try to exploit the system by indulging in collusion, identity fraud etc. We term such nodes as ‘non-reciprocating nodes’ and prohibit such behavior by proposing the “Give-and-Take” criterion, where exchange is allowed iff each participating node provides at least one segment to the node which is unavailable with the node. While complying with this criterion, each node wants to maximize its utility, which depends on the node’s segment set available with the node. Link activation between pair of nodes requires mutual consent of the participating nodes. Each node tries to find a pairing partner by preferentially exploring nodes for link formation. Unpaired nodes download data segments using the expensive link with pre-defined probability (defined as segment aggressiveness probability). We present various linear complexity decentralized algorithms based on the Stable Roommates Problem that can be used by nodes for choosing the best strategy based on available information. We present a decentralized randomized algorithm that is asymptotically optimal in the number of nodes. We define Price of Choice for benchmarking the performance of social groups consisting of non-aggressive nodes (i.e. nodes not downloading data segments from the expensive link) only. We evaluate performances of various algorithms and characterize the behavioral regime that will yield best results for nodes and social groups, spending the least on the expensive link. The proposed algorithms are compared with the optimal. We find that the Link For Sure algorithm performs nearly optimally.     

Network Formation for Asymmetric Players and Bilateral Contracting

We study a network formation game where players wish to send traffic to other players. Players can be seen as nodes of an undirected graph whose edges are defined by contracts between the corresponding players. Each player can contract bilaterally with others to form bidirectional links or break unilaterally contracts to eliminate the corresponding links. Our model is an extension of the traffic routing model considered in Arcaute, E., Johari, R., Mannor, S., (IEEE Trans. Automat. Contr. 54(8), 1765–1778 2009) in which we do not require the traffic to be uniform and all-to-all. Player i specifies the amount of traffic t_ij ≥ 0 that wants to send to player j. Our notion of stability is the network pairwise Nash stability, when no node wishes to deviate unilaterally and no pair of nodes can obtain benefit from deviating bilaterally. We show a characterization of the topologies that are pairwise Nash stable for a given traffic matrix. We prove that the best response problem is NP-hard and devise a myopic dynamics so that the deviation of the active node can be computed in polynomial time. We show the convergence of the dynamics to pairwise Nash configurations, when the contracting functions are anti-symmetric and affine, and that the expected convergence time is polynomial in the number of nodes when the node activation process is uniform.     

Time versus cost tradeoffs for deterministic rendezvous in networks

Two mobile agents, starting from different nodes of a network at possibly different times, have to meet at the same node. This problem is known as rendezvous. Agents move in synchronous rounds. Each agent has a distinct integer label from the set \(\{1,\ldots ,L\}\). Two main efficiency measures of rendezvous are its time (the number of rounds until the meeting) and its cost (the total number of edge traversals). We investigate tradeoffs between these two measures. A natural benchmark for both time and cost of rendezvous in a network is the number of edge traversals needed for visiting all nodes of the network, called the exploration time. Hence we express the time and cost of rendezvous as functions of an upper bound E on the time of exploration (where E and a corresponding exploration procedure are known to both agents) and of the size L of the label space. We present two natural rendezvous algorithms. Algorithm Cheap has cost O(E) (and, in fact, a version of this algorithm for the model where the agents start simultaneously has cost exactly E) and time O(EL). Algorithm Fast has both time and cost \(O(E\log L)\). Our main contributions are lower bounds showing that, perhaps surprisingly, these two algorithms capture the tradeoffs between time and cost of rendezvous almost tightly. We show that any deterministic rendezvous algorithm of cost asymptotically E (i.e., of cost \(E+o(E)\)) must have time \(\varOmega (EL)\). On the other hand, we show that any deterministic rendezvous algorithm with time complexity \(O(E\log L)\) must have cost \(\varOmega (E\log L)\).     

Towards professionally user-adaptive large medical image transmission processing in mobile telemedicine systems

To effectively and efficiently reduce the transmission costs of large medical image in (mobile) telemedicine systems, we design and implement a professionally user-adaptive large medical image transmission method called UMIT. Before transmission, a preprocessing step is first conducted to obtain the optimal image block (IB) replicas based on the users’ professional preference model and the network bandwidth at a master node. After that, the candidate IBs are transmitted via slave nodes according to the transmission priorities. Finally, the IBs can be reconstructed and displayed at the users’ devices. The proposed method includes three enabling techniques: (1) user’s preference degree derivation of the medically useful areas, (2) an optimal IB replica storage scheme, and (3) an adaptive and robust multi-resolution-based IB replica selection and transmission method. The experimental results show that the performance of our proposed UMIT method is both efficient and effective, minimizing the response time by decreasing the network transmission cost.     

Asymptotic assessments of CRC error probabilities in some telecommunication protocols

We study the value distributions for the control cyclic redundancy check (CRC) of length k, drawn at the data section of volume n. The behavior of CRC value distribution is examined at large n and fixed values of k (k = const, n → ∞). With the application of the character theory, we find the conditions of asymptomatic uniformity of the CRC distribution. The asymptomatic results can be applied during the assessment of errors of a series of protocols such as USB, X.25, HDLC, Bluetooth, Ethernet, etc.     

Rendezvous in networks in spite of delay faults

Two mobile agents, starting from different nodes of an unknown network, have to meet at a node. Agents move in synchronous rounds using a deterministic algorithm. Each agent has a different label, which it can use in the execution of the algorithm, but it does not know the label of the other agent. Agents do not know any bound on the size of the network. In each round an agent decides if it remains idle or if it wants to move to one of the adjacent nodes. Agents are subject to delay faults: if an agent incurs a fault in a given round, it remains in the current node, regardless of its decision. If it planned to move and the fault happened, the agent is aware of it. We consider three scenarios of fault distribution: random (independently in each round and for each agent with constant probability \(0<p<1\)), unbounded adversarial (the adversary can delay an agent for an arbitrary finite number of consecutive rounds) and bounded adversarial (the adversary can delay an agent for at most c consecutive rounds, where c is unknown to the agents). The quality measure of a rendezvous algorithm is its cost, which is the total number of edge traversals. For random faults, we show an algorithm with cost polynomial in the size n of the network and polylogarithmic in the larger label L, which achieves rendezvous with very high probability in arbitrary networks. By contrast, for unbounded adversarial faults we show that rendezvous is not possible, even in the class of rings. Under this scenario we give a rendezvous algorithm with cost \(O(n\ell )\), where \(\ell \) is the smaller label, working in arbitrary trees, and we show that \(\varOmega (\ell )\) is the lower bound on rendezvous cost, even for the two-node tree. For bounded adversarial faults, we give a rendezvous algorithm working for arbitrary networks, with cost polynomial in n, and logarithmic in the bound c and in the larger label L.     

Analysis of YouTube’s traffic adaptation to dynamic environments

The popular Internet service, YouTube, has adopted by default the HyperText Markup Language version 5 (HTML5). With this adoption, YouTube has moved to Dynamic Adaptive Streaming over HTTP (DASH) as Adaptive BitRate (ABR) video streaming technology. Furthermore, rate adaptation in DASH is solely receiver-driven. This issue motivates this work to make a deep analysis of YouTube’s particular DASH implementation. Firstly, this article provides a state of the art about DASH and adaptive streaming technology, and also YouTube traffic characterization related work. Secondly, this paper describes a new methodology and test-bed for YouTube’s DASH implementation traffic characterization and performance measurement. This methodology and test-bed do not make use of proxies and, moreover, they are able to cope with YouTube traffic redirections. Finally, a set of experimental results are provided, involving a dataset of 310 YouTube’s videos. The depicted results show a YouTube’s traffic pattern characterization and a discussion about allowed download bandwidth, YouTube’s consumed bitrate and quality of the video. Moreover, the obtained results are cross-validated with the analysis of HTTP requests performed by YouTube’s video player. The outcomes of this article are applicable in the field of Quality of Service (QoS) and Quality of Experience (QoE) management. This is valuable information for Internet Service Providers (ISPs), because QoS management based on assured download bandwidth can be used in order to provide a target end-user’s QoE when YouTube service is being consumed.     

Reducing the Range of Perception in Multi-agent Patrolling Strategies

Multi-Agent Patrolling Problems consist in moving agents throughout a graph in order to optimize a collective performance metric. Some strategies from the literature tackle this problem by dispatching decentralized autonomous agents that coordinate themselves merely by sensing and writing information in the nodes. In this work, they are called k-range local strategies, were k indicates the range, in number of edges, of the agents’ sensing capabilities. The 1-range strategies (where agents can sense up to its neighbor nodes) are certainly the most common case in the literature. And only few 0-range strategies (where agents can only sense its current node) were found, although this type of strategy has the advantage of requiring simpler hardware, when applied in the design of real robots. In this work, we propose two higher-level procedures to reduce the perception range of 1-range strategies to 0: the Zr Method and the EZr Method. Applying both methods in 1-range strategies found in the literature, we created twenty new 0-range strategies, which were evaluated in a simulation experiment described and analyzed here. We also developed a prototype of a low-cost patrolling robot that is able to run the 0-range strategies proposed in this work.     

Partial and complete local diagnosis in computer systems with circulant structure

System diagnosis at multiple faults of multiplicity not greater than t is considered. The conditions when the state of each system module is only determined by the testing rusults of the physically connected modules (self-determination conditions) are analysed. The diagnosability conditions are established for the case when the self-determination conditions are not satisfied for any module. A new class of locally (t _r /t)-diagnosable systems is introduced, where t is the fault multiplicity and t _r is the multiplicity of faults at which the states of all system modules can be determined correctly and completely. The values of t _r are estimated. It is shown that the local t-diagnosability can be achieved by the system test redundancy.