In this paper we discuss how to determine the appropriate order when recommending new friends or new interests based on the confidence scores generated by using SVM on a social network. The main idea is analyzing the ego's friendship circles to find interests or friends which are not currently included in their profile, and then the confidence scores obtained by SVM are used to decide which interests or friends should be recommended in every turn, based on the focal individual's network structure, also called an ego network. The novel factor in this approach is that it does not make recommendations using a fixed order. This is because a fixed order would make some improper recommendations, then mislead next recommendation, and obtain increasingly less accuracy results. In our experiments, it is shown that the accuracy achieved when using our confidence score order is better than that with a fixed order, even when there is very little information contained in a person's profile.

In this paper, we focus on finding out the parameter setting of the non-decreasing sponsored search auction (NDSSA) such that the produced outcome is satisfied by both the search engine provider (SEP) and advertisers. Six satisfaction factors are included in our problem formulation. The outcome satisfactions of the SEP and advertisers are modeled as the multi-objective optimization problem based on the satisfaction factors. The weighted versions of L2-norm, cosine similarity, and Euclidean distance are proposed to solve the multi-objective problem. We observe the outcome without bias for both participants in our simulation. Both cosine similarity and Euclidean distance show that SEP and advertisers prefer fixed-MIP to AIMD. Moreover, the initial MIP value should be set as small enough such that each advertiser has at least one opportunity to update his/her bid price.

The IEEE 802.16 standard is defined to meet the high-speed and wide-range data transmission in an efficient way. This paper studies the scheduling problem on IEEE 802.16e mesh networks to minimize the energy consumption of mobile stations so as to maximize the network lifetime. We consider the real-time connections and focus on the resource scheduling which includes time slots allocation, QoS guarantee of real-time flows, interference-free on each link, and spectral reuse for the channel. The proposed energy-aware link scheduling algorithms construct a mathematical model of the energy consumption problem and provide a computationally efficient scheme to solve the optimization problem. Comparing with traditional scheduling schemes for real-time flows, simulation results show that the proposed scheme significantly improves the life cycle of mobile stations.

Determining winners in combinatorial auctions is an NP-complete problem. Based on the idea of searching Nash Equilibria (NE), this paper presents a local search procedure to determine winners. To improve the solution quality calculated by the local search, we propose Nash Equilibrium Search Approach (NESA) to probe various NE solutions. According to the simulation results, auctioneer¡¦s revenue in NESA is at least 1.08% and 9.10% more than that in a general GA and Casanova, respectively. A stable solution based on NESA will be obtained within 400 seconds. Moreover, simulation results show that the solution quality of NESA is near-optimal.

A mobicast, or called as mobile geocast, problem in three-dimensional (3D) underwater sensor networks (USNs) is investigated in this paper, which aims to overcome the hole problem and minimizes the energy consumption of the sensor nodes while maximizing the data collection. In this work, all underwater sensor nodes are randomly distributed in a 3D underwater environment in the sea to form a 3D USN. Considered a mobile sink or an AUV (autonomous underwater vehicle), all possible sensor nodes near to the AUV form a 3D geographic zone (called as 3D zone of reference or 3D ZOR). The AUV travels a user-defined route and continuously collects data form sensor nodes within a series of 3D ZORs at different time. The main problem is how to efficiently collect data from sensor nodes within a 3D ZOR while those sensor nodes are usually in sleep mode for a long period of time. The routing protocol relies on two phases; the first phase is to collect data form sensor nodes within a 3D ZOR, and the second phase is to wake up those sensor nodes in the next 3D ZOR to be queried while trying to avoid topology holes. To save power, only sensor nodes in a 3D ZOR are notified to enter the active mode in order to deliver sensed results to the AUV. To consider the characteristics of USNs, a new mobicast routing protocol is developed in 3D USNs. The key design challenge is to develop a power-saving mobicast protocol in 3D USNs to overcome the unpredictable 3D hole problem. An ”apple slice” technique is used to build multiple segments to surround a hole and to assure routing path continuity. Finally, performance analysis is derived and simulation results illustrate the performance improvement in successful delivery rate and power consumption.

In this paper, we present a spatiotemporal multicast, called a mobicast, protocol for supporting applications which require spatiotemporal coordination in VANETs. The spatiotemporal character of a mobicast is to forward a mobicast message to vehicles located in some geographic zone at time t, where the geographic zone is denoted as zone of relevance (ZOR). Vehicles located in ZOR at the time t must keep the connectivity to maintain the real-time data communication between all vehicles in ZOR. The temporal network fragmentation problem is occurred if the connectivity of ZOR is lost such that vehicles in ZOR cannot successfully receive the mobicast messages. To solve the problem, a new mobicast protocol is presented in this work to successfully disseminate mobicast messages to all vehicles in ZOR via a special geographic zone, called as zone of forwarding (ZOF). The main contribution of this work is to develop a new mobicast routing protocol to dynamically estimate the accurate ZOF to successfully disseminate mobicast messages to all vehicles in ZOR. To illustrate the performance achievement, simulation results are examined in terms of dissemination successful rate, packet overhead multiplication, and packet delivery delay.

For the current technique, the tuning latency ¿ on each transmitter is more than the packet transmission time, and it cannot be ignored in packet scheduling. So in order to reduce the serious affection of tuning operations, we propose the multi-hop model for the All-to-All Broadcast (AAB) problem in WDM optical star networks with N nodes and w available wavelengths, which the number of hop distance for packet transmissions is limited to a constant ¿. Our strategy can overlap the tuning latency in multi-hop scheduling, and reduce the number of tuning operations on each transmitter to 2¿(w - 1)/¿¿. If ¿ can be completely covered in scheduling, the schedule length is k(k - 1) + ¿ + 2¿(w-1)/¿¿[k2¿(¿+1)/2] time slots, where k = N/w. Otherwise, it is k(k - 1) + ¿ + 2¿(w-1)/¿¿[k¿(¿+1)/2 + ¿] slots. Our proposed method is very suitable for the scalable WDM networks if the number of wavelength is fixed, and its multi-hop schedule length is shorter than that of other scheduling approaches if k is small or ¿ is larger.

In WDM-based network, a single fiber abortion may cause many logical lightpaths failures such that embedded logical topology of a WDM network may become disconnected. And a hung amount of data of a single link carried is lost by this link errors. For this reason, we propose an efficient survivable routing approach, which is based on the technique of ear-decomposition, to create protected routing of the embedded logical topology that can withstand a physical link failure. Our approach divides the logical topology into several ears, and restricts the lightpaths of the same ear are routed by using disjoint physical links. To solve the survivable problem is NP-complete and we formulate the survivable routing problem as an ILP problem based on the results of ear decomposition. And our experiments has shown that the solution generated from our ILP achieves the following two results: (I) a high performance in terms of the survivable routing and (2) a better performance than previous research results for the balance of traffic loads.

The problem of minimum congestion hypergraph embedding in a cycle (MCHEC) is to embed the hyperedges of a hypergraph as adjacent paths around a cycle, such that the maximum congestion over any physical link in the cycle is minimized. The problem is NP-complete in general, but solvable in polynomial time when all hyperedges contain exactly two vertices. In this paper, we first formulate the problem as an integer linear program (ILP). Then, a solution with approximation bound of 1.5(opt + 1) is presented by using a clockwise (2/3)-rounding algorithm, where opt denotes the optimal value of maximum congestion. To our knowledge, this is the best approximation bound known for the MCHEC problem.

The problem of connecting a set of terminals that lie on the sides of a rectangle to minimize the total area is discussed. An O ( n ) algorithm is presented to solve this problem when the set of n terminals is initially sorted. The strategy in this paper is to reduce the problem to several problems such that no matter what instance is started with, at least one of these problems can be solved optimally by a greedy method.

The problem of connecting a set of n terminals belonging to m (signal) nets that lie on the sides of a rectangle to minimize the total area is discussed. We present an $O(n(m + \log n))$approximation algorithm to solve this problem. Our algorithm generates a solution with area $ \leqq 1.6 * {\operatorname{OPT}}$, where ${\operatorname{OPT}}$ is the area of an optimal solution. The nets are routed according to the following greedy strategy: the wire connecting all points from a net is one whose path crosses the least number of corners of the rectangle. For some nets there are several routes that cross the least number of corners. A subset of these nets is connected by wires whose paths blend with the paths for other nets. The remaining nets are routed using several strategies and $2^6 $ layouts are obtained. The best of these layouts is the solution generated by our algorithm.

The problem of connecting a set of terminals that lie on the sides of a rectangle to minimize the total area is discussed. We present an O(nm) approximation algorithm to solve this problem where n is the number of terminals and m is the number of signal nets. Our algorithm generates a solution with an area ≤1.69* OPT where OPT is the area of an optimal solution. Our algorithm routes some of the nets by a simple greedy strategy. The remaining nets are routed using several strategies and four layouts are obtained. The best of these layouts is the solution generated by our algorithm.