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In the recent years, resource virtualization technologies of different types have been widely used in the ICT industry, particularly in cloud computing domain. These virtualization technologies can squeeze out hardware potential and consequently can significantly save CAPEX and OPEX. Virtualization technologies are adopted in network emulation to emulate heterogeneous nodes of target networks. At present, network emulators typically utilize legacy x86-based virtual machines (VMs) and light-weighted containers to emulate network nodes of heterogeneous architectures including ARM, SPARC, PPC, etc., which introduces software incompatibility to the original system software, protocols and applications, and may consequently jeopardize emulation fidelity. This paper focuses on mitigating the emulation incompatibility problem caused by node heterogeneity. Firstly, this problem is thoroughly investigated and analyzed on a cloud-based network emulation platform. Then, a hybrid virtualization approach concurrently utilizing multiple virtualization technologies, namely KVM, QEMU, and Docker to emulate heterogeneously architected nodes is derived and then implemented in the cloud-based network emulation platform. Functional verification and performance evaluation experiments have been carried out and have led to the conclusion that the elaborated hybrid virtualization approach can effectively dispose of the emulation incompatibility problem with affordable performance degradations. In addition, a case study of applying the hybrid virtualization approach to emulate a space-ground integrated network (SGIN) is conducted to show its effectivity and efficiency.

We propose finite difference methods for solving two dimensional Hamilton–Jacobi–Bellman (HJB) equations and systems arising from the modelling of transboundary pollution with emission permits trading. We prove that our numerical scheme for the HJB equations from cooperative game is consistent, stable, and monotone, therefore guarantees convergence to viscosity solutions. To ensure our scheme is fully implicit and unconditionally monotone, we combine wide stencil with narrow stencil in the discretization. We address coupling between unknown variables and emission controls using policy iteration. We solve the coupled systems of HJB equations from non-cooperative game efficiently through policy-like iteration. We give a theoretical analysis of our scheme for solving the coupled system and find that it converges under certain conditions. Finally, we show that our numerical scheme achieves higher order of convergence than the finite volume method proposed originally.

Public key cryptographic primitive (e.g., the famous Diffie-Hellman key agreement, or public key encryption) has recently been used as a standard building block in authenticated key agreement (AKA) constructions for wireless sensor networks (WSNs) to provide perfect forward secrecy (PFS), where the expensive cryptographic operation (i.e., exponentiation calculation) is involved. However, realizing such complex computation on resource-constrained wireless sensors is inefficient and even impossible on some devices. In this work, we introduce a new AKA scheme with PFS for WSNs without using any public key cryptographic primitive. To achieve PFS, we rely on a new dynamic one-time authentication credential that is regularly updated in each session. In particular, each value of the authentication credential is wisely associated with at most one session key that enables us to fulfill the security goal of PFS. Furthermore, the proposed scheme enables the principals to identify whether they have been impersonated previously. We highlight that our scheme can be very efficiently implemented on sensors since only hash function and XOR operation are required.

In order to meet the needs of real-time services in the low-orbit communication network, the paper draws on the related research of edge computing technology in the ground broadband network and applies it to the LEO satellite constellation communication network, sinking the processing power of the backend cloud center (CC) to the nodes close to the user terminals, thereby reducing the response delay of the task and the bandwidth consumption of the backhaul network in the LEO constellation networks. This paper proposes a sever selection strategy based on queuing theory and weighting method. For the computing offload requests submitted by frontend users, this strategy first regards the nearest accessing satellite edge computing node as the first choice to offload computing tasks; if it is not qualified, then synthetically consider various factors, such as the total energy consumption of the data transmission and calculation for the request, the load balancing among the computing nodes, and the response delay to the user, etc. These factors for candidate computing nodes are scored separately, and the all-around score is finally used to select the most suitable computation offloading node. Comprehensive simulation experiments show that, compared with another two approaches, the proposed strategy can ensure that user requests are well satisfied, and can reduce the average response delay in the range from 17% up to 34%.

The combination of edge computing and LEO satellite broadband network has the potential to provide ground users enhanced services with significantly lower latencies. This paper derives a offloading model and a user model of LEO satellite constellation networks and proposes a multi-level computation offloading scheme. This scheme designs a multilevel edge-projection pursuit (MLEPP) model and uses an optimization method to find the optimized projection direction in order to obtain the most suitable offloading choices. On the other hand, a discrete event-based Monte Carlo simulator is developed to evaluate the proposed computation offloading scheme. Comparative evaluation experiments have been conducted, and the results indicate that, in resource-restricted scenarios, using the derived multi-level offloading scheme can effectively and efficiently decrease the average request blocking probability, the average request corresponding delay, and keep the average request cost at a restricted level.

The study presents a new efficient way to construct the one-round key exchange (ORKE) without random oracles based on standard hard complexity assumptions. The authors propose a (PKI-based) ORKE protocol which is more computational efficient than existing pairing-based ORKE protocols without random oracles in the post-specified peer setting. The core idea of this construction is to integrate the consistency check of the ephemeral public key and the verification of the signature into the session key generation. This enables us to roughly save two pairing operations. The authors just call this kind of scheme that is deeply composed by signature and one-round key exchange as SignORKE. The authors’ protocol is shown to be secure in a variant of the Canetti–Krawczyk security model which covers the majority of state-of-the-art active attacks.

Information Centric Networking (ICN) is a promising future networking architecture, and Named Data Networking (NDN) is considered to be its authoritative and representative scheme. In recent years, applying ICN/NDN concept in Mobile Ad-hoc Network (MANET), i.e. Name Data Mobile Ad-hoc Network (NDMANET), becomes a research hotspot. Compared with traditional IP protocol, NDN scheme is thought to be more robust and profitable to the node mobility and dynamically changed topologies in MANET. This paper focuses on NDMANET’s in-networking caching strategy, which provides a great flexibility and efficiency for data dissemination and is a vital feature of NDMANET. Firstly, the paper investigates and analyzes some existing caching strategies which are widely applied in the ICN/NDN domain. On that basis, a novel Content Popularity and Distance based Interval (CPDI) caching strategy is derived for NDMANET, with the purpose of improving its network performance. Comprehensive simulation experiments have been carried out and the results illustrate that the proposed CPDI caching strategy can introduce considerable improvements on the average cache hit ratio, the average number of cached data packets, and the average energy consumption with only slightly degrading the average download delay.

Network emulation is an essential method to test network architecture, protocol and application software during a network’s entire life-cycle. Compared with simulation and test-bed methods, network emulation possesses the advantages of accuracy and cost-efficiency. However, legacy network emulators are typically restricted in scalability, agility, and extensibility, which builds barriers to prevent them from being widely used. In this paper, we introduce the currently prevalent cloud computing and related technologies including resource virtualization, NFV (network functional virtualization), SDN (software-defined networking), traffic control and flow steering to the network emulation domain. We design and implement an innovative cloud-based network emulation platform, aiming at providing users Network Emulation as a Service (NEaaS), which can be conveniently deployed on both public and private clouds. We carried out performance evaluation and discussion on this platform. It turns out, the platform can significantly outperform most legacy network emulators regarding to the scalability, agility, and extensibility, with much lower emulation costs.

In the last decade, various resource virtualization technologies have been widely applied in ICT industry, particularly the cloud computing domain. These virtualization technologies can squeeze out hardware potential and consequently can save expenditure. Virtualization technologies are used in the network emulation domain to emulate network nodes, which could be quite heterogeneous in terms of hardware architecture. Currently, many network emulators utilize x86 based virtual machines (VMs) to emulate target network nodes of heterogeneous architectures, i.e. ARM, SPARC, PPC, etc., which may introduce incompatibility to the original system and application software of the target nodes, and will consequently jeopardize the emulation fidelity. This paper focuses on alleviating the emulation incompatibility caused by node heterogeneity. Firstly, this emulation incompatibility problem is investigated and analyzed. Then, a hybrid virtualization approach to emulate heterogeneous nodes is elaborated and implemented in a cloud-based network emulation system. A case study of applying the proposed approach to emulate a space-ground integrated network (SGIN) is conducted. Functional verification and performance evaluation experiments lead to the results, which show the hybrid approach can effectively dispose of the incompatibility problem with an affordable performance degradation.

The cost of formal health care and the caregiver burden introduced by the increasingly aging population pose a drasticchallenge to our society. The efforts to find solutions to address this issue have fosteredAmbient Assisted Living (AAL)as a novel technology discipline, the aim of which is to exploit the potentials provided bythe emerginginformation and communication technologies tohelp the aged and recovering people keep an active, independent and safe lifestyle in their daily routine. In recent years, the progress in health sensing, wireless communication, smart home, cloud computing, andassistive robotics has essentially helped the vision of AAL to become a reality. Many research efforts in AAL have been carried out and made significant advances in the development of AALsystems, services, and applicationsin the areas such as the daily task facilitation, mobility assistance, and the rehabilitation. The goal of this Feature Topic is to explore the recent research activities related to AAL and attract the attention of the academic and industrial communities for developing advanced and innovative methodologies and techniques of AAL.

Summary In the recent past, television (TV) industry has started to provide users with ultra high definition (ultra-HD) and/or 3-dimensional TV programs, which on the one hand, can bring users greatly enhanced viewing experience, while on the other hand, considerably increases the transmission bandwidth requirements and may lead to bandwidth shortage situations in many different types of TV systems. In particular, this bandwidth shortage poses a serious challenge in the current satellite TV broadcasting systems because of the strictly limited bandwidth available in C and Ku frequency bands. Aiming at mitigating the bandwidth shortage problem, this paper proposes an innovative mixed channel transmission scheme for the next generation satellite TV systems. The proposed scheme integrates the merits of using both broadcast and multicast methods, both Ku and Ka frequency bands, as well as both wide-shaped and spot antenna beam types. According to the conducted comprehensive simulation experiments, this mixed scheme is able to effectively enhance the frequency bandwidth utilization with still providing users affordable quality of experience. Moreover, to cope with the impact brought by ever increasing number of provided TV channels, this paper enhances the proposed scheme by using multicast method to transmit those least popular global channels, which can efficiently reduce the quality of experience degradation up to 90% in Ku- and Ka-band frequency resource restricted scenarios.