Pre-computation based selective probing (PCSP) scheme with imprecise state information

We propose a new distributed QoS routing scheme called PCSP that uses pre-computation based selective probing for routing decisions. This algorithm pre-computes the cost and QoS metrics respectively for the least cost and the best QoS paths. The pre-computed information enables to strictly limit the set of neighboring nodes involved in the probing process, thereby reducing the message complexity without sacrificing cost optimality. Computer simulation reveals that the PCSP scheme indeed has low message complexity and high success ratio with guaranteed optimal search.

The goal of quality-of-service (QoS) routing is to find a network path which has sufficient resources to satisfy certain constraints on delay, bandwidth and/or other metrics. The network state information maintained at every node is often imprecise in a dynamic environment because of nonnegligible propagation delay of state messages, periodic updates due to overhead concern, and hierarchical state aggregation. The information imprecision makes QoS routing difficult. The traditional shortest-path routing algorithm does not provide satisfactory performance with imprecise state information. We propose a distributed routing scheme, called ticket-based probing, which searches multiple paths in parallel for a satisfactory one. The scheme is designed to work with imprecise state information. It allows the dynamic trade-off between the routing performance and the overhead. The state information of intermediate nodes is collectively used to guide the routing messages along the most appropriate paths in order to maximize the success probability. The proposed algorithm consider not only the QoS requirements but also the cost optimality of the routing path. Extensive simulations show that our algorithm achieve high call-admission ratio and low-cost routing paths with modest overhead. The algorithm can tolerate high degree of information imprecision.

Due to mobility in wireless networks, the state information of all outgoing links (link delays, available resources and costs) of nodes is imprecise. Fuzzy logic has proven to be a powerful tool when dealing with imprecise information. The implemented distributed protocol incorporates fuzzy inference systems to guide the process of finding routes with sufficient resources to satisfy a certain delay and other requirements with least end-to-end cost in a dynamic network. Multi-path parallel search is used to increase the probability of finding a feasible path. When there are such multiple paths, the one with least cost is selected. Results show how this protocol can tolerate a high degree of information imprecision. Success ratios for delay resource constrained routing reach values over 92%.

Since the nodes in mobile ad hoc network act as a router and host, the routing protocol is the primary issue and has to be supported before any applications can be deployed for ad hoc wireless network. In recent years much work has been done on routing in ad hoc networks. But most of them couldn't provide the quality-of-service (QoS). Considering the characters of dynamic topology and the imprecise state information in mobile ad hoc network, we propose an extension QoS routing algorithm based on dynamic source routing (DSR) protocol while adopting fuzzy logic to select the appropriate QoS routing in multiple paths which are searched in parallel. The algorithm can tolerate a high degree of information imprecision by adding the fuzzy logic module which integrates the QoS requirements of application and the routing QoS parameters to determine the most qualified one in every node. This scheme considers not only the bandwidth and end-to-end delay of routing, but also the cost of the path. So it also may improve the network performance. On the other hand the merit of using fuzzy logic is that it can be implemented by hardware. This makes the realization of the scheme easier and faster. However our algorithm is based on DSR, the maximal hop count should be less than 10, i.e., the scale of mobile ad hoc network should not be very large.

A model for the calculation of Potential Ecological Network at regional level has been presented in this paper. Through the use of GIS techniques and Natural Protected Areas and Land Use Map GIS datasets, the proposed model links two Ecological Network approaches (Species-Specific and Land Units) using the Least - Cost Path (LCP) algorithm. The nodes of the Ecological Potential Network have been analyzed using the Graph Theory. Specific GIS workflows have been set up to model the ecological connectivity in problematic mapping conditions, such as under road bridges and on the riverbanks. The main workflow requires a rasterization of the input datasets to allow the LCP algorithm application. The variations of the pixel resolution have been analyzed in terms of accuracy of the output and computation time of the model. The results underline an emerging property of Potential Ecological Networks, the Secondary Nodes, which are a set of nodes at the intersection of Linkages built by the LCP algorithm.

Afek, Awerbuch, Plotkin, and Saks identified an important fundamental problem inherent to distributed networks, which they called the Resource Controller problem. Consider, first, the problem in which one node (called the root) is required to estimate the number of events that occurred all over the network. This counting problem can be viewed as a useful variant of the heavily studied and used task of topology update (that deals with collecting all remote information). The Resource Controller problem generalizes the counting problem: such remote events are considered as requests, and the counting node, i.e., the root, also issues permits for the requests. That way, the number of request granted can be controlled (bounded).An efficient Resource Controller was constructed in the paper by Afek et al., which can operate on a dynamic network assuming that the network is spanned by a tree that may only grow, and only by allowing leaves to join the tree. In contrast, the Resource Controller presented here can operate under a more general dynamic model, allowing the spanning tree of the network to undergo both insertions and deletions of both leaves and internal nodes. Despite the more dynamic network model we allow, the message complexity of our controller is always at most the message complexity of the more restricted controller.All the applications for the controller of Afek et al. apply also for our controller. Moreover, with the same message complexity, our controller can handle these applications under the more general dynamic model mentioned above. In particular, under the more general dynamic model, the new controller can be transformed into an efficient size-estimation protocol, i.e., a protocol allowing the root to maintain a constant estimation of the number of nodes in the dynamically changing network. Informally, the resulted new size-estimation protocol uses O(log2n) amortized message complexity per topological change (assuming that the number of changes in the network size is too small), where n is the current number of nodes in the network. In addition, with the same message complexity (as that of the size-estimation protocol), the new controller can be used to solve the name-assignment problem by assigning and maintaining unique log n+O(1)-bit identifiers for the nodes of the dynamic network.The new size-estimation protocol can be used for other applications, not mentioned in the paper by Afek et al.. Specifically, it can be used to extend many existing labeling schemes supporting different queries (e.g routing, ancestry, etc.) so that these schemes can now operate correctly also under more general models. These extensions maintain the same asymptotic sizes of the corresponding labels (or routing tables) of the original schemes and incur only a relatively low extra additive cost to the message complexity of the corresponding original schemes.

In this paper, a hop-by-hop Quality-of-Service (QoS) routing mechanism is proposed to maintain the routing performance in networks with imprecise link state information. The proposed mechanism, Normal- PI, applies statistical methods to compute two-sided simultaneous prediction intervals from sampled history of the available bandwidths. A QoS metric - statistical available bandwidth - is then generated from the prediction interval. This metric replaces the instantaneous available bandwidth in the ordinary widest-shortest path routing algorithm (WSR). Simulation results demonstrate that the Normal-PI achieves much less update message overhead compared to WSR without deteriorating the routing performance in terms of packet loss and link utilization.

We describe distributed tracking of a nonlinear dynamical system via networked sensors. The sensors communicate with each other by means of a multihop protocol over a communication network. We derive in-network processing algorithms to deal with arbitrary network topology and then extend these results to account for communication delays and packet losses. We show that these algorithms are optimal in the linear setting and achieve centralized performance. The proposed techniques differ from existing techniques in two important aspects: a) there is no designated leader/fusion node and each sensor attempts to optimally track the system trajectory based on its local observations and time-dependent information available from other sensors in the network; b) the message computation at each sensor is structurally identical. Consequently, the sensor network can be queried at any time and at any node to obtain optimal estimates for the state of the dynamical system. We then present two multihop protocols - one based on gossip and another token-based - for distributed implementation of the in-network processing techniques. We show several advantages of token-based schemes over gossip protocols: a) message complexity is significantly smaller for achieving the same performance; b) they are well-suited for situations where target and network data aggregation time-scales are comparable; and c) they are well-suited for random geometric graphs with nodes having small communication-connectivity radius - a scenario typical of ad-hoc wireless networks. This is because they can fuse data only from the set of nodes that can be visited in any time period.

QMBF: a QoS-aware multicast routing protocol

Algorithm for multi-constrained path selection based on experimental analysis

Distributed Computation of Connected Dominating Set for Multi-Hop Wireless Networks

We consider a server serving a time-slotted queued system of multiple packet-based flows, where not more than one flow can be serviced in a single time slot. The flows have exogenous packet arrivals and time-varying service rates. At each time, the server can observe instantaneous service rates for only a subset of flows (selected from a fixed collection of observable subsets) before scheduling a flow in the subset for service. We are interested in queue length aware scheduling to keep the queues short. The limited availability of instantaneous service rate information requires the scheduler to make a careful choice of which subset of service rates to sample. We develop scheduling algorithms that use only partial service rate information from subsets of channels, and that minimize the likelihood of queue overflow in the system. Specifically, we present a new joint subset-sampling and scheduling algorithm called Max-Exp that uses only the current queue lengths to pick a subset of flows, and subsequently schedules a flow using the Exponential rule. When the collection of observable subsets is disjoint, we show that Max-Exp achieves the best exponential decay rate, among all scheduling algorithms that base their decision on the current (or any finite past history of) system state, of the tail of the longest queue. To accomplish this, we employ novel analytical techniques for studying the performance of scheduling algorithms using partial state, which may be of independent interest. These include new sample-path large deviations results for processes obtained by non-random, predictable sampling of sequences of independent and identically distributed random variables. A consequence of these results is that scheduling with partial state information yields a rate function significantly different from scheduling with full channel information. In the special case when the observable subsets are singleton flows, i.e., when there is effectively no a priori channel state information, Max-Exp reduces to simply serving the flow with the longest queue; thus, our results show that to always serve the longest queue in the absence of any channel state information is large deviations optimal.

The article reveals the legal positions of the Constitutional Court of Ukraine regarding everyone’s right to information. Attention is focused on information that is collected by state authorities, local self-government bodies, institutions and organizations, and which is not a state or other secret protected by the Law of Ukraine «On Information» and which every person has the right to familiarize himself with. Separate attention is focused on confidential information (information with limited access). One of the types of confidential information is medical information, which, on the one hand, in special cases provided for by the Fundamentals of the Health Care Legislation of Ukraine, can be disclosed to family members or a legal representative of the patient, and on the other hand, in accordance with the decision of the European Court of Human Rights person in the case of «M.K. against Ukraine» confirmation by a doctor of a patient’s illness to a member of his family, even if he learned about it from the patient himself, is an interference by the state in a person’s right to private life, and in the case of infectious diseases, it is qualified as not carried out «in accordance with the law». Attention is focused on the fact that such situations arise more and more when military personnel undergo medical examinations and that there are prohibitive norms of a special law that forbid the disclosure of medical information regarding a certain list of diseases of a military personnel to his employer (military unit), commander, family members of the military personnel. Regarding the confidentiality of information and about a person who holds a position related to the performance of the functions of the state, local self-government bodies, and about members of his family, the legal positions of the Constitutional Court of Ukraine are established: absolutely in each specific case it is determined whether information about a person belongs to confidential; there are guarantees of protection of the rights of the above-mentioned persons, and additional legal burdens, and therefore the state is called upon to ensure a balance of public and private interest. The article also draws attention to the fact that even under martial law conditions, control (direct; indirect) by institutions of public power is prohibited both in terms of content and dissemination of information, even if the state pursues such a goal as protecting the information space from what is considered harmful by the state information that is not necessary for society. The practice of the Constitutional Court of Ukraine on this issue is established. Attention is focused on the fact that censorship cannot be used in Ukraine to protect the information field of the state even in war conditions - it is prohibited in part 3 of Art. 15 of the Constitution of Ukraine.

In this paper, we consider delay-optimal power control for an energy harvesting wireless system with finite energy storage. The system is powered solely by a renewable energy source with bursty data arrivals, and is characterized by data and energy queues. We consider delay-optimal power control and formulate an infinite horizon average cost Markov Decision Process (MDP). To deal with the curse of dimensionality, we introduce a virtual continuous time system and derive closed-form approximate priority functions for the MDP at various operating regimes. Based on the approximation, we obtain a low complexity online power control solution which is adaptive to the channel state information as well as the data and energy queue state information. The derived power control solution has a multilevel water-filling structure, where the water level is determined jointly by the data and energy queue lengths.

Transportation is a huge problem that curbs development of societies and economy in many countries nowadays. Participatory sensing technologies encourage people to be involved in environment monitoring through smart devices. Vehicle sensor networks (VSNs) are a novel solution for road event detection with advantages. In this paper, we consider runtime road event detection using VSNs to satisfy the application-specific requirements through collaboration among vehicles. A group road detection scheme (GRD) by using dynamic clustering in VSNs is presented to improve detection performance with low time complexity and message complexity. The simulations with testbed of 5 remote controllable vehicles show that GRD scheme provides effectiveness under different road scenarios.