Robust wireless communication between devices is crucial to ensuring the reliability of IoT systems. However, it is strictly relied on estimating the link quality of these devices, which is usually interfered with by environmental factors. In such a scenario, intelligent algorithms based on machine learning to select resistant communication links are promising solutions, but they demand sophisticated computation, limiting their deployment on resource-constrained IoT devices. Therefore, this paper introduces a lightweight link quality estimation algorithm, namely LLQE, built from the gradient boosting decision tree. The superiority of our proposal not only precisely assesses several levels of link quality but also is lightweight enough for resource-constraint devices. The evaluation results on publicly available datasets show that LLQE accurately estimates various link quality indicators with 97% accuracy.

Intelligent offloading of computation-intensive tasks to a mobile cloud server provides an effective mean to expand the usability of wireless devices and prolong their battery life, especially for low-cost internet-of-things (IoT) devices. However, realization of this technology in multiple-input multiple-output (MIMO) systems requires sophisticated design of joint computation offloading and other network functions such as channel state information (CSI) estimation, beamforming, and resource allocation. In this paper, we study the computation task offloading and resource allocation optimization in MIMO based mobile edge computing systems considering perfect/imperfect-CSI estimation. Our design aims to minimize the maximum weighted energy consumption subject to practical constraints on available computing and radio resources and allowable latency. The optimal and low-complexity algorithms are proposed to solve the underlying mixed integer non-linear problems (MINLP). For the perfect-CSI, we employ bisection search to find the optimal solution. The low-complexity algorithms are developed by decomposing the original optimization problem into the offloading optimization (OP) and power allocation (PA) subproblems and solve them iteratively. Moreover, the difference of convex functions (DC) method is employed to deal with non-convex structure of (PA) subproblems in the imperfect-CSI scenario. Numerical results confirm the advantages of proposed designs over conventional local computation strategies in energy saving and fairness.

Mobile ad-hoc networks (MANETs) have attracted extensive research interests over the past several years due to its multi-hop, self-organized characteristics, leading to a new application domain: instant and fast-deployed ad-hoc services without any network infrastructures. Many testbeds for protocol evaluation have been designed and developed toward this trend. In this paper, we review the pros and cons of each testbed in order to find the appropriate one for developing further. Unfortunately, the existing testbeds support only for the out-dated wireless network devices and be discontinued supporting. Widening the type of supported wireless network devices and protocols is a vital option for a MANET testbed, ManetPRO is proposed and designed for protocol evaluation. ManetPRO will work over a variety of wireless network devices and support many network protocols.

There exists a plethora of work about information dissemination and routing in Wireless Sensor Networks (WSNs), but no work tries to aggregate all this research and connect it all together. This paper, however, reviews WSN research and presents a two-tier framework that can be used to classify alternative approaches and techniques. This framework includes: i) logical network architecture for information dissemination, and ii) physical network infrastructure and routing.

An increasing number of research efforts on wireless sensor networks (WSNs) are now considering dynamic environments with heterogeneous sensor devices. Most of this research considers data, control, and management issues separately and not clearly within a common architecture. This paper presents our development of an architecture, namely DCM-Arch, to address these issues together. The architectureconsists of three-planes of functionalities (in the verticaldimension): 1) data, 2) control, and 3) management; and four-tiers of network infrastructures (in the horizontal dimension): 1) routing and network infrastructure, 2) logical network infrastructure, 3) adaptation middleware, and 4) component-based software application. The data plane handles the information storage, reduction, and dissemination in WSNs. The control plane deals with the lightweight sensor adaptation and reconfiguration middleware to cope with the dynamic changes of the environment. Finally, the management plane provides the context management functions, e.g. for collaboration and reasoning, to allow sensors, coordinators, and sinks to make good decisions about adaptation and reconfiguration. While the vertical dimension describes the functionalities of DCM-Arch, its four-tiers provide the required facilities to achieve those functionalities.

There is a large body of work addressing information storage, reduction, and dissemination in Wireless Sensor Networks (WSNs), but there seems to be no contribution giving a survey of this literature. In this paper we take on such a challenge and review previous WSN research and further presents a framework that we use for classifying the different proposed approaches and techniques. The framework is structured into 3 tiers: (1) routing and network infrastructure, (2) logical network infrastructure, and (3) information storage and processing. The paper, however, mainly focuses on tier-2 and tier-3. We also discuss future visions and challenges within the WSN community.

The paper first gives an overview of the required functions for providing Internet connectivity and mobility management for mobile ad-hoc networks (MANETs). Internet gateway selection is one of these functions. Since multiple Internet gateways might exist on the same MANET domain, a hybrid metric for Internet gateway selection is proposed as a replacement of the shortest hop-count metric. The hybrid metric provides load-balancing of intra/inter-MANET traffic. Simulation results show that ad-hoc routing protocols, using our proposed metric get better performance in terms of packet delivery ratio and transmission delay, at the cost of slightly increased signalling overhead.

This paper presents the ongoing researches towards the implementation and the performance evaluation of our proposed BGP-GCR+ routing architecture via simulation in ns-2. BGP-GCR+ consists of three components: (1) a two-level hierarchical, non-overlapped, one-node fault-tolerant routing algorithm for large-scale mobile ad-hoc networks (MANETs), (2) an IPv6-based address stateless auto-configuration scheme, and (3) procedures at Internet gateways between autonomous systems (ASs) to select backup or load-balancing routes through MANETs. We have implemented the first component of BGP- GCR+ into ns-2 for performance evaluation. Simulation results show that the packet delivery ratio in BGP-GCR+ is slightly lower than that in the ad-hoc on-demand distance vector (AODV) for the high-mobility, small-scale (50-150 nodes), but higher for the medium-scale (200 nodes) MANETs. Moreover, the routing overhead is lower in BGP-GCR+ compared with AODV.