Abstract Roaming service is required in the ubiquitous access used in the global mobility networks (GLOMONETs) and the security is one of the most important issues. Many researchers focus their interests on authentication schemes for GLOMONETs. In 2015, Gope and Hwang, Zhang et al. and Farash et al. proposed their key agreement authentication schemes for GLOMONETs, respectively. However, we find weaknesses in them. Gope and Hwang’s scheme is under the off-line guessing attack and the de-synchronization attack. Moreover, it does not keep strong forward security and the session key is known by the home agent. Zhang et al.’s scheme has several weaknesses including vulnerability to the off-line guessing attack, destitution of password change phase, and the leakage of updated session key. Farash et al.’s scheme lacks user anonymity and strong forward secrecy and is vulnerable to the off-line password guessing attack. The session key is known to the home agent, too. Furthermore, neither Gope and Hwang’s scheme nor Farash et al.’s scheme has the session key update phase. To eliminate the problems, we present an improved authentication and key agreement scheme for GLOMONETs. According to the formal proof and the informal analysis, our scheme is well-performed and applicable.

Keywords Global mobility network, User anonymity, Formal proof, Mutual authentication.

Abstract Motivated by the geolocation requirements of future mobile network applications such as portable internet of things (IoT) devices and automated airborne drone systems, this paper aims to provide techniques for improving device geolocation estimates in urban and indoor locations. In these applications low size, weight and power are vital design constraints. This paper proposes methods for improving the geolocation estimate available to a system in indoor and urban environments without the need for addition sensing or transmitting hardware. This paper proposes novel system application techniques that enable the integration of signals of opportunity, providing a robust geolocation estimate without any additional hardware. The proposed method utilises a sinusoidal Kalman filter architecture to analyse raw radio frequency (RF) signals that surround a system in urban and indoor environments. The introduced techniques efficiently analyse the raw RF data from any signal of opportunity and combine it with higher level geolocation sensors to provide an improved geolocation estimate. The improvements achieved by the system in a range of environments have been simulated, analysed and compared to the results obtained using the prior art. These improvements have been further validated and benchmarked by hardware test. The results obtained provide evidence that the efficient use of signals of opportunity coupled with common navigation sensors can provide a robust and reliable geolocation system in indoor and urban environments.

Keywords Signals of opportunity, Kalman filtering, Radio navigation and geolocation.

Abstract Nowadays, tremendous growth of Internet of Things (IoT) applications is seen in smart environments such as medical remote care applications which are crucial due to the general aging of the population. With the recent advancements in IoT-based healthcare technologies, activity recognition can be used as the key part of the intelligent healthcare systems to monitor elderly people to live independently at homes and promote a better care. Recently, the evidence theory and its derivates approaches began to take place in the fields of activity recognition in these smart systems. However, these approaches are generally inconsistent with the probability calculus due to the lower and upper probability bounds considering the combined evidences. To overcome these challenges and to get more precisely the reconcilement between the evidence theory with the frequentist approach of probability calculus, this work proposes a new methodology for combining beliefs, addressing some of the disadvantages exhibited by the evidence theory and its derivatives. This methodology merges the non-normalized conjunctive and the majority rules. The proposed rule is evaluated in numerical simulation case studies involving the activity recognition in a smart home environment. The results show that this strategy produces intuitive results in favor of the more committed hypothesis.

Abstract In this paper, we exploit cooperative communication for designing an energy-efficient routing algorithm in underwater wireless sensor networks (UWSNs). Each network node is equipped with a single omnidirectional antenna and multiple node coordinates while taking advantage of spatial diversity. This research work is limited in scope to amplify-and-forward (AF) scheme at the relay node and fixed ratio combining (FRC) strategy at the receiver node. Cooperative diversity at the physical layer and multi-hop routing at the network layer enable us to formulate minimum energy routing as a joint optimization of the transmission power at physical layer and link selection at the network layer. Simulations results show that our proposed cooperative energy-efficient routing for UWSN (Co-EEUWSN) performs better than the selected non-cooperative routing protocols (depth-based routing (DBR) and energy-efficient DBR (EEDBR)) and cooperative DBR (Co-DBR) in terms of packet delivery ratio, end-to-end delay, and energy efficiency.

Abstract Neighborhood discovery is a fundamental link layer service for safety and non-safety applications in VANETs. Till now, this service is made available by beaconing. But, several studies demonstrate its inefficiency. In the literature, several papers propose adaptive strategies to alleviate the channel load problem, but packet loss due to collision remains an open issue due to the randomness of beacon sending through the network. In this paper, we propose an SDMA-based beaconing with load balancing method that distributes beacon sending load fairly. In the proposed scheme, the vehicles self-organize themselves into groups depending on their positions. Then, all beacons are sent sequentially along the period, thereby reducing the congestion. We drive extensive simulations to demonstrate the effectiveness of our strategy.

Abstract The Internet evolved from a network with a few terminals to an intractable network of millions of nodes. Recent interest in information-centric networks (ICNs) is gaining significant momentum as a Future Internet paradigm. The key question is, hence, how to model the massive amount of connected nodes with their content requests in dynamic paradigm. In this paper, we present a novel method to characterize data requests based on content demand ellipse (CDE), focusing on efficient content access and distribution as opposed to mere communication between data consumers and publishers. We employ an approach of a promising eminence, where requests are characterized by type and popularity. Significant case studies are used to demonstrate that critical properties of ellipses may be used to characterize the content request irregularity during peak times. Depending on the degree of irregularity, the curve we plot becomes elliptic with a positive eccentricity less than one and an orientation centered with a bias. Real traffic data have been used to demonstrate how various data demand/request types affect eccentricity, orientation, and bias. Through simulations, we propose a dynamic resource allocation framework for Virtual Data Repeaters (VDRs) by correlating the resource allocation schema with the factors that affect the CDE in ICN.

Abstract Area monitoring using Internet and barrier coverage is a typical application of wireless sensor networks. The main concerns in this type of applications are coverage efficiency and sensor energy conservation. For that, many activities scheduling algorithms are proposed in the literature. Unlike prior efforts based on an unrealistic binary sensor coverage model, this paper proposes three efficient activities scheduling algorithms based on realistic sensor coverage models. The first algorithm (C1L-PBC) is centralized and it is based on a coverage graph. The second algorithm (D1L-PBC) is distributed and it ensures 1-barrier coverage; whereas, the third one (D2L-PBC) is also distributed and it guarantees 2-barrier coverage. The obtained experimental results show that the proposed algorithms can effectively guarantee the barrier coverage and prolong the sensor network lifetime.