Understanding node mobility is critical for the proper simulation of mobile devices in a wireless network. However, current mobility models often do not reflect the realistic movements of users within their environments. They also do not provide the freedom to adjust their degrees of randomness or adequately mimic human movements by injecting possible crossing points and adding recurrent patterns. In this paper, we propose the recurrent self-similar Gauss–Markov mobility (RSSGM) model, a novel mobility model that is suitable for applications in which nodes exhibit recurrent visits to selected locations with semi-similar routes. Examples of such applications include daily human routines, airplane and public transportation routes, and intra-campus student walks. First, we present the proposed algorithm and its assumptions, and then we study its behavior in different scenarios. The study’s results show that different and more realistic mobility traces can be achieved without the need for complex computational models or existing GPS records. Our model can flexibly adjust its behavior to fit any application by carefully tuning and choosing the right values for its parameters.
Network function virtualization (NFV) and software-defined networking (SDN) are two technologies that have emerged to reduce capital and operational costs, and to simplify network management. In this paper, we propose an SDN-based system that provisions virtual network functions (VNFs) to minimize round trip time (RTT) delay and synchronization delay requirements. Our system uses graphic-theoretic approaches to place newly requested VNFs including four centrality functions -betweenness, degree, closeness, and Katz. The system performance is evaluated using two random graph topologies representing the physical and logical structures. The impact of increasing the number of deployed VNFs is considered. The results indicate that the degree and Katz selection methods mostly provide the minimum RTT for physical networks, whereas the betweenness selection provides minimum RTT values for logical networks. Moreover, the closeness selection method provides the best synchronization delay for both logical and physical networks.
This paper contributes to the challenging field of security for wireless sensor networks by introducing akeyagreement scheme in which sensor nodes create secure radio connections with their neighboursdepending on the aidof third parties. These third parties are responsible only for the pair-wise keyestablishment among sensor nodes,so they do not observe the physical phenomenon nor route data packetsto other nodes. The proposed methodis explained here with respect to four important issues: how secretshares are distributed, how local neighboursare discovered, how legitimate third parties are verified, andhow secure channels are established. Moreover, theperformance of the scheme is analyzed with regards tofive metrics: local connectivity, resistance to node capture,memory usage, communication overhead, andcomputational burden.Our scheme not only secures the transmissionchannels of nodes but also guaranteeshigh local connectivity of the sensor network, low usage of memory resources,perfect network resilienceagainst node capture, and complete prevention against impersonation attacks. As it isdemonstrated in thispaper, using a number of third parties equals to 10% of the total number of sensor nodes inthe area ofinterest, the proposed method can achieve at least 99.42% local connectivity with a very low usageofavailable storage resources (less than 385 bits on each sensor node)
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