Recently, low Earth orbit (LEO) satellites have been suggested as a promising solution for global coverage of 5G networks. However, long propagation delay makes obtained channel state information (CSI) (which is employed for efficient spectrum utilization) outdated before usage. Note that CSI is closely related to elevation angle and relative location. Although elevation angle and relative location could be estimated by terrestrial device position and LEO ephemeris, maintaining these two informations requires a high cost for most IoT devices. Due to regular and high-speed orbital movement of LEO, for an arbitrary terrestrial device, LEOs repeat the same behavioral pattern (e.g., satellite rise and satellite set) again and again. Satellite rise and set result in different temporal correlations in elevation angle and relative location. By the aid of the temporal correlations mentioned above, we proposed a CSI prediction scheme for satellite-terrestrial networks without terrestrial device position and LEO ephemeris. Simulation results show that our scheme has a rather low prediction error under various LEO altitude/obit, terrestrial device location/mobility, ground environments, weather, and elevation angle when handover.

To improve throughput, 5G networks adopts beamforming technique and have high small-cell-density deployment. In Time Division Duplex (TDD) based 5G networks, Almost Blank Subframes (ABS) scheme and Cell Range Expansion (CRE) scheme are adopted to reduce inter-cell interference and to achieve inter-cell load balancing, respectively. However, existing ABS allocation and CRE are cell-based, i.e., requires that all beams inside a cell adopting the same ABS allocation. Due to the multiple overlapping of small cells, such cell-based ABS/CRE may much reduce the throughput. In this paper, we proposed a beam-based ABS allocation and beam-based CRE. To further reduce the interference, in this paper, small cell center UEs and small cell edge UEs (those UEs connects to small cell due to CRE technique) have distinct downlink schedules. According to our simulation results, our scheme have low computation cost since the computation cost of beam-based is much lower than cell-based.

In software-defined networking (SDN), network rules are installed in ternary content-addressable memory (TCAM). TCAM is a scarce and expensive resource which is a bottleneck for scaling SDN. Rule distribution is a strategy to solve the TCAM shortage problem, which decomposes a large table stored at network ingress into a number of smaller sub-tables and distributes them across network switches. Rule distribution includes two sub-problems, sub-table allocation, and table decomposition. Sub-table allocation is to guarantee that each flow path passes all the partitioned sub-tables and maximize the number of partitioned sub-tables (for reducing the size of sub-tables). Table decomposition problem is to partition a large rule table into a number of balanced sub-tables and reduce the rules overhead. In this paper, we propose a sub-table allocation algorithm and size-balancing sub-table partition algorithm. Simulation results show that the performance of both algorithms is better than previous works in terms of reducing the TCAM entries used in each switch.

In this paper, we study a new problem called probabilistic k-weighted coverage placement, which is a generalization of the Q-coverage placement. Q-coverage placement assumes that the monitored area has uniform coverage requirement: events within the monitored area should be detected with probability Q × 100% (i.e., detected by Q sensors), while probabilistic k-weighted coverage placement assumes that the monitored area has k-degrees of coverage requirement (i.e., k kinds of detection probability): events within distinct region of the monitored area are detected with distinct detection ability, i.e., one of the k kinds of detection probability. Besides, Q-coverage placement requires that the coverage requirement is integer multiple of 100% detection probability, while probabilistic k-weighted coverage placement allows coverage requirement to be non-integer multiple of 100% detection probability. We derive a lower bound on the number of sensors needed to satisfy the coverage requirement of a probabilistic k-weighted monitored area, and introduce a greedy algorithm to solve the problem.

Since traffic engineering (TE) in Software Defined Networking (SDN) can be much more efficiently and intelligently implemented, Multipath in SDN becomes a new option. However, Ternary Content Addressable Memory (TCAM) size become the bottleneck of SDN. In this paper, we propose an SDN-based Dynamic Flowentry-Saving Multipath (DFSM) mechanism for inter-DC WAN traffic forwarding. DFSM adopts source-destination-based multipath forwarding and latency-aware flow-based traffic splitting to save flow entries and achieve better load balancing. Our evaluations indicate that DFSM saves 15% to 30% system flow entries in different topologies compared to label-based tunneling, and also reduces average latency by 10% to 48% by consuming 8% to 20% more flow entries than Equal-Cost Multipath (ECMP) in less-interconnected topologies. In addition, compared to even traffic splitting, DFSM reduces the standard deviation of path latencies from 14% to 7%.

In cognitive radio networks (CRNs), channel hopping-based communications are widely used to improve channel utilization. However, channel hopping schemes for CRNs are usually vulnerable to jamming attacks, especially when jammers have cognitive radios to perform channel sensing and fast channel switching. Many mitigating approaches for coping with jamming attacks in wireless communications rely on pre-shared secrets (e.g., pre-shared hopping sequences). In CRNs, pre-sharing secrets between senders and receivers is usually impractical (because neighborhood dynamically changes, and receivers of a broadcast may be unknown to the sender). Hence, anti-jamming channel hopping approaches without pre-shared secrets have gained more and more research interests. However, existing approaches either have unbounded time to rendezvous on an available channel (even no signals of jammers and PUs appear), or require role pre-assignment (SUs should be pre-assigned as a sender or receiver). Role pre-assignment is not applicable to environments where each SU may play a sender and a receiver, simultaneously. In this paper, we propose an antijamming channel hopping scheme, Sec-CH. Sec-CH has bounded time to rendezvous and can work without role pre-assignment.

Jamming attack is one of the major threats in cognitive radio networks (CRNs). In this paper, we propose an anti-jamming channel hopping algorithm, Tri-CH, for CRNs. Tri-CH adopts random jump pattern (i.e., hops randomly over channels) to achieve high security level and reception mode stay pattern (i.e., stays at a channel for receiving packets only) to guarantee bounded time to rendezvous. Tri-CH operates without pre-shared secrets and role pre-assignment. Hence, Tri-CH is applicable to large networks, where nodes join and leave the network frequently, and may play the sender role and the receiver role, simultaneously. According to the theoretical analysis, Tri-CH outperforms in terms of maximum time to rendezvous under jamming attacks.

In cognitive radio networks, unlicensed users [secondary users (SU)] need to rendezvous on licensed channels before establishing communication links. Dedicated common control channel is the simplest way to achieve rendezvous. However, due to the absolute priority of licensed users [primary users (PU)] on accessing licensed channels, a dedicated common control channel may cause the PU long-time blocking problem, and the control channel saturation problem in a high SU density environment. Channel hopping schemes have been proposed to avoid the problems mentioned above. In this paper, we introduce two quorum-based channel hopping schemes. Our schemes outperform in terms of the four metrics: maximum time to rendezvous, channel loading, degree of rendezvous, and maximum conditional time to rendezvous.

(t, k)-Diagnosis, which is a generalization of sequential diagnosis, requires that at least k faulty processors be identified and repaired in each iteration when there are at most t faulty processors, where t ≥ k. Based on the assumption that each vertex is adjacent to at least one fault-free vertex, the conditional (t, k)-diagnosis of graphs was investigated by using the comparison diagnosis model. Lower bounds on the conditional (t, k)-diagnosability of graphs were derived, and applied to obtain the following results. 1) Symmetric d-dimensional grids are conditionally (N/2d+1 -1, 2d -1)-diagnosable when d ≥ 2 and N (the number of vertices) ≥ 4d. 2) Symmetric d-dimensional tori are conditionally (1/5 (N + min{8/5 N2/3, 2N-20/15} - 2), 6)-diagnosable when d = 2 and N ≥ 49 and ( N/2d+1 -1, 4d-2)-diagnosable when d ≥ 3 and N ≤ 4d. 3) Cube-connected cycles are conditionally (N/4 - 1, 4)-diagnosable. 4) k-ary trees are conditionally (N/k+1 - 1)-diagnosable.

Range-free localization approaches are cost-effective for mobile sensor networks (because no additional hardware support is required). However, existing range-free localization approaches for mobile sensor networks suffer from either sparse anchor node problem or high communication cost. Due to economic considerations, mobile sensor networks typically have sparse anchor nodes which makes most range-free localization algorithms inaccurate. On the other hand, due to the power limitation of mobile sensor nodes (i.e., they are battery-operated) and high power consumption by communication, high communication cost will significantly reduce the network life time. For solving these two problems, in this paper, we use historical beacons (i.e., anchor nodes' announcements delivered in previous time slots) and received signal strength (RSS) to derive three constraints. By the aid of the three constraints, we introduce a low-communication-cost range-free localization algorithm (only one-hop beacon broadcasting is required). According to the theoretical analysis and simulation results, our three constraints can indeed improve the accuracy. Simulation results also show that our algorithm outperforms even in irregular-radio-signal environments. In addition, a hardware implementation running on sensor nodes, Octopus Xs, confirms theoretical analysis and simulation results.

Cognitive radio networks (CRNs) have emerged as a critical technique for solving spectrum shortage problems and enhancing the utilization of licensed channels. To prevent interference with the co-locate incumbent networks, before data transmission, nodes in CRNs should rendezvous on an available channel (i.e., idle licensed channel) for establishing a link or exchanging control information. However, implementing rendezvous is challenging because the availability of channels is time-varying and position-varying. For reducing rendezvous failure and increasing throughput, a node pair in CRN should be able to rendezvous on every licensed channels (i.e., maximizing rendezvous diversity) and rendezvous on an available channel as soon as possible (i.e., minimizing maximum conditional time to rendezvous (MCTTR)). Besides, to take full advantage of the frequency diversity of multi-channel medium access, rendezvous should be spread out in time and channel (i.e., minimizing channel loading). In this paper, we propose two rendezvous channel hopping algorithms, T-CH and D-CH, which can be used without time synchronization and role pre-assignment (each node has a pre-assigned role as either a sender or a receiver). D-CH requires that SUs in CRNs should have a unique ID (identifier), while T-CH does not. Both our T-CH and D-CH have maximum rendezvous diversity and minimum channel loading, and outperform in terms of MCTTR.

Uncoordinated frequency hopping has been considered as an important technique for anti-jamming communications. In uncoordinated frequency hopping systems, nodes randomly switch over multiple frequencies without pre-shared keys. Upon rendezvous on the same frequency, they can communicate with each other. Existing algorithms, however, require role (sender/receiver) pre-assignment before frequency hopping. Such approaches only support the communication between sender-receiver pairs (i.e., the communication between a node pair whose receiver play a sender role is not guaranteed). In this paper, we propose a low computation cost and symmetric-role frequency hopping algorithm (i.e., no role pre-assignment requirement). Our proposed algorithm has bounded maximal time to rendezvous under asynchronous scenarios.

Jamming attacks have become wireless security threats disrupting reliable RF communication. Frequency Hopping Spread Spectrum (FHSS) is a widely used technique for anti-jamming wireless communications. However, FHSS relies on the pre-shared secret key between the communication pair. However, secure key exchange is challenging. Recently, Uncoordinated Frequency Hopping (UFH) schemes have been studied to achieve resilient key establishment in presence of a jammer. However, existing UFH schemes either suffer from unguaranteed rendezvous. In this paper, we introduce an Jamming-Resilient Asynchronous-Symmetric UFH scheme, AJCH, for guaranteeing rendezvous.

Recently, cognitive radio (CR) has become a key technology for addressing spectrum scarcity. In CR networks, spectrum access should not interfere the colocate incumbent networks. Due to the requirement above, common control channel approaches, which are widely used in traditional multichannel environments, may face serious CR long-time blocking problem and control channel saturation problem. Although channel-hopping-based approaches can avoid these two problems, existing works still have significant drawbacks including long time-to-rendezvous, unbalance channel loading, and low channel utilization. In this paper, we introduce three channel-hopping approaches, RCCH, ARCH, and SARCH for synchronous and asynchronous environments, respectively. Compared with previous works, our schemes outperform the state of the art in terms of these metrics.

In mobile wireless sensor networks, it is important to understand the moving pattern of sensor nodes. There are a lot of application that need sensors nearby to co-work, such as data centric applications. Thus, knowing the co-moving nodes will be helpful to these applications. In this paper, we propose a co-moving sensor nodes detection algorithm based on virtual coordinate system. We use the geometric property of independent set to build our virtual coordinate system. The computation cost of building a virtual coordinate in this way is low and the result is relative accurate - just a coordinate rotation will it matches true coordinates. With the aids of virtual coordinate system, we can find out co-moving sensor node pairs efficiently and no precise localization scheme needed (for each sensor) in our works.

The problem of coverage is a fundamental issue in wireless sensor networks. In this article, we consider two subproblems: k -coverage contour evaluation and k -coverage rate deployment. The former aims to evaluate, up to k , the coverage level of any location inside a monitored area, while the latter aims to determine the locations of a given set of sensors to guarantee the maximum increment of k -coverage rate when they are deployed into the area. For the k -coverage contour evaluation problem, a nonuniform-grid-based approach is proposed. We prove that the computation cost of our approach is at most the square root of existing solutions. Based on our k -coverage contour evaluation scheme, a greedy k -coverage rate deployment scheme ( k -CRD) is proposed, which is shown to be an order faster than existing studies for k -coverage rate deployment. The k -CRD can incorporate two different heuristics to further reduce its running time. Simulation results show that k -CRD with these heuristics can be significantly more time efficient without causing much degradation in the coverage rate of final deployment.

In this paper, assuming that each vertex is neighboring to at least one fault-free vertex, we investigate the (t,k)-diagnosability of a graph G under the PMC model. Lower bounds on the numeric degrees of (t,k)-diagnosability are suggested when G is a general graph or G is a regular graph. In particular, the following results are obtained. Symmetric d-dimensional grids are ({N-m\over 2d}, {\min} \{m, 2d-1\} )-diagnosable, where d\ge 2, 1\le m\le 2d-1, and N are the number of vertices. Symmetric d-dimensional tori are ({N+0.62 N^{{2\over 3} }-2\over 4},1)-diagnosable if d=2, and ({N-m\over 2d}, {\min} \{m, 4d-2\} )-diagnosable if d\ge 3, where 1\le m\le 4d-2. Hypercubes are ({N-2\log N+2\over \log N},2\log N-2)-diagnosable. Cube-connected cycles are ({N-m\over 3}, {\min} \{m, 4\} )-diagnosable, where 1\le m \le 4; k-ary trees are ({N-1\over k}, 1)-diagnosable.

In this paper, we propose a zoom-based approach for parking space availability. The main idea of our scheme lies on the fact that drivers near the queried locations are interested in detail (zoomed-in) parking space information, while drivers in a distant place are interested in rough (zoomed-out) information about free parking spaces. Our zooming technique is based on discrete cosine transform. Besides, a winner-take-all scheme is also proposed to further reduce communication overhead in packet loss environment. As compared to previous work, simulation results show that our scheme reduces 40% to 50% communication overhead.

In this paper, a distributed taxi hailing protocol in vehicular ad-hoc networks (VANET) is suggested. Our protocol consists of two parts: taxi booking and taxi de- blocking. Taxi booking part ensures that a vacant taxi with shortest driving distance to passenger under real traffic regulations is booked. Taxi de-blocking part aims to de-block blocked vacant taxis as soon as possible. Simulation results show that compared with previous results, at least 40% of booking time, 50% of waiting time of passengers and 50% of driving distance from booked taxi to passenger, is reduced in our protocol.

Most of routing protocols in VANETs are position-based due to their well scalability. The forwarding decisions of such protocols are simply based on the location information of forwarders' neighborhood and the destination node. Due to high mobility of vehicles, location-service protocols are required to provide the destination location. Location services protocols can be categorized as flooding-based and quorum-based. They are unrealistic for VANETs. In the former approaches, global network flooding require extreme high cost, while in the latter approaches, quorums' hand-off is impossible because of high volume of exchange data. In this paper, we present a routing by utilizing locality of vehicles' traces (i.e., left location information). Besides, by the aid of high mobility of vehicles and news exchange (new information about vehicles' location), vehicles' location information can be spread to improve the possibility of meeting a vehicle which has the location information of the destination. Our protocol is realistic and practical because neither global network flooding nor quorums are required. The simulation results show that our protocol works efficiently for VANETs in city environments and has higher successful query rate and lower cost.

In this paper, we propose a realistic resource sharing protocol for VANET. The main idea of our protocol comes from typhoons. Typhoons move according to their eyes' mobility, i.e., quorums which are responsible for a given resource holder/requester "moves" according to the resource holder's/ requester's mobility. Our protocol exploits spatial locality between requesters and resource holders. When resource requesters get their desired resources, they are able to be new resource holders. For hot-resources, requesters are so numerous that the spatial locality is much enhanced over time. Besides, lots of applications (e.g., available parking slot information) in VANET are location-aware which have spatial locality between requesters and resource holders. By the aid of the spatial locality, resource holders/requesters share/query sources in their vicinity in our protocol. Simulation results show that our protocol has lower search latency and well scalability comparing to the previous work. Besides, due to that the spatial locality is enhanced over time, successful rate increases over time.

System-level diagnosis aims to identify faulty processors in a multiprocessor system by means of analyzing the test results among the processors. (t, k)-Diagnosis, which is one of the most important system-level diagnosis strategies, requires at least k faulty processors identified in each iteration provided there are at most t faulty processors, where t ≥ k. In this paper, a new (t, k)-diagnosis algorithm for regular networks is proposed. Experimental results show that the proposed algorithm has larger values of t for tori and matching composition networks, in comparison with previous (t, k)-diagnosis algorithms.

How to route packets efficiently and reliably is an important issue in Vehicular Ad hoc Networks (VANETs). Due to the high mobility of vehicles, the communication topology of vehicles in VANET changes rapidly. In this paper, a Virtual Landmarks-based approach is suggested. Under the assistant of Virtual Landmarks, an efficient path is guaranteed even if the roads topology is complex. Our approach is applicable to routing packets between a vehicle and static destination. Simulation results shows that in comparison with previous work, our approach has much lowest communication cost and guarantees a reliable path.

Coverage problem is a fundamental issue in wireless sensor networks. In this paper, we consider two sub-problems: k-coverage rate evaluation and k-coverage rate deployment. The former aims to evaluate the ratio of k-covered area relative to the monitored area, while the latter aims to determine the minimum number of sensors required and their locations to guarantee that k-coverage rate of the monitored area meets application requirements. For k-coverage rate evaluation problem, a non-uniform-grid- based approach for random deployments is proposed. For k-coverage rate deployment problem, a greedy-based approach is suggested to meet the requirement of k-coverage rate. Simulation results show that both our schemes are more time efficient than previous work.

(t, k)-diagnosis, which is a generalization of sequential diagnosis, requires at least k faulty processors identified and replaced (or repaired) in each iteration provided there are at most t faulty processors, where $t \ge k$. This paper suggests lower bounds on the degrees of $(t,k)$-diagnosability of multiprocessor systems under both the PMC and the MM* models. As a consequence, grids and tori of d dimensions are shown to be $(\Omega(N^\frac{d}{d+1})$, $\Omega(d))$-diagnosable and $(\Omega(N^\frac{d}{d+1})$, $\Omega(2d))$-diagnosable, respectively, where N is the number of processors.

A new diagnosis strategy called c-step diagnosis is proposed. A system is c-step t-diagnosable if all faulty units within the system can be identified and repaired in at most c iterations provided the number of faulty units present does not exceed t. The upper bound and the lower bound on the c-step diagnosabilities were derived. Moreover, an upper bound on c was suggested

(t, k)-diagnosis, which is a generalization of sequential diagnosis, requires at least k faulty processors identified and replaced in each iteration provided there are at most t faulty processors, where t /spl ges/k This paper proposes a (t,k) diagnosis algorithm for matching composition networks, which include many well-known interconnection networks such as hypercubes, crossed cubes, twisted cubes, and Mobius cubes. It is shown that matching composition networks of n dimensions are (/spl Omega/(2/sup n//spl middot/logn/n),n)-diagnosable, where n > 5.

In this paper, we study diagnosabilities of multiprocessor systems under two diagnosis models: the PMC model and the comparison model. In each model, we further consider two different diagnosis strategies: the precise diagnosis strategy proposed by Preparata et al. and the pessimistic diagnosis strategy proposed by Friedman. The main result of this paper is to determine diagnosabilities of regular networks with certain conditions, which include several widely used multiprocessor systems such as variants of hypercubes and many others.