Efficient task and resource allocation techniques are critical to managing the relationships between the components of cloud, fog, and mist-assisted Internet of Things networks. Fulfilling this function necessarily implicates concerns between two affected groups, users, who prioritize cost-effectiveness and latency, and service providers, who prioritize efficient and cost-effective resource management. While there is no single solution that is capable of simultaneously wholly optimizing the experiences of both groups, solutions that ensure mutual satisfaction can be achieved. To accomplish this, we developed an algorithm that first derives two objective functions, user and service provider satisfaction, from data concerning service provisioning, user preferences, and resources utilization. The algorithm then combines these functions into a mutual objective function that maximizes satisfaction of both individuals. Next, available computing nodes are ordered in a list, prioritizing by compromising factors, and the most appropriate node(s) for task completion are selected. The proposed algorithm was tested extensively through simulations and compared with existing techniques. Ultimately, the proposed algorithm outperformed alternatives across every metric, illustrating its utility as a means of achieving mutual satisfaction and improving quality of service.

Data/tasks of Industrial Internet of Things (IIoT) are extremely private and valuable to computing. Edge computing facilitates IIoT services by offering platforms of supportive facilities and functionalities. However, the convergence of intelligent edge computing and IIoT platforms has been held back by the need to develop systems for maintaining security and privacy. In this article, we propose a new framework for securely and confidentially sending, storing, and computing IIoT tasks. This framework employs a lightweight encryption scheme alongside modified ElGamal encryption and digital signature schemes. We analyzed the robustness of this framework in terms of security and privacy, and assessed its performance through simulations. Ultimately, the proposed framework outperformed the existing models in terms of time complexity, latency, and energy consumption.

Improving quality of service (QoS) of low power and lossy networks (LLNs) in Internet of things (IoT) is a major challenge. Cluster-based routing technique is an effective approach to achieve this goal. This paper proposes a QoS-aware clustering-based routing (QACR) mechanism for LLNs in Fog-enabled IoT which provides a clustering, a cluster head (CH) election, and a routing path selection technique. The clustering adopts the community detection algorithm that partitions the network into clusters with available nodes' connectivity. The CH election and relay node selection both are weighted by the rank of the nodes which take node's energy, received signal strength, link quality, and number of cluster members into consideration as the ranking metrics. The number of CHs in a cluster is adaptive and varied according to a cluster state to balance the energy consumption of nodes. Besides, the protocol uses the CH role handover technique during CH election that decreases the control messages for the periodic election and cluster formation in detail. An evaluation of the QACR has performed through simulations for various scenarios. The obtained results show that the QACR improves the QoS in terms of packet delivery ratio, latency, and network lifetime compared to the existing protocols.

UAS (Unmanned Aerial Systems) are now drawing a lot of attention from academic and research fields as well as the general public. The UAS is expected to provide many promising applications such as intelligent transportation system, disaster management, search and rescue, public safety, smart delivery, wild species monitoring, and wireless service area extension. More specifically, as a part of the wireless service extension, we deal with the information dissemination and collection using a UAV in this paper. In this application, because the UAV communicates with each CH (Cluster Head) to collect data from sensor nodes or to disseminate information to the sensor nodes, well-behaved and qualified nodes should be elected as CHs and their integrity should be preserved. Even though a UAV makes the information dissemination and collection process efficient in a WSN, we can make the UAV help the election of new CHs to mitigate the threat of compromised CHs. To this aim, we first propose a UAV-aided CH election framework where a UAV delivers the critical information collected from sensors to the sink, and the sink reselects a set of well-behaved and qualified CHs considering the information. Then, we classify the existing security-driven CH election schemes into several categories and explain the principle of each category and its representative schemes. For each representative scheme, we also explain how to adapt it into the UAV-aided CH election framework. Next, we identify some desirable security properties that a CH election scheme should provide and reveal the security level that each representative scheme reaches for the desirable security properties. Next, we compare communication and computation overhead of the security-driven CH election schemes in terms of the big O notation. In conclusion, we reveal what we have learned from this survey work and provide a future work item.

In wireless sensor networks, clustering is frequently adopted because it facilitates the energy savings of nodes and consequently extends the network lifetime. In this paper, we propose a novel and secure cluster formation scheme. First, our scheme generates larger sized clusters to raise the quality of clusters. Second, our scheme produces healthier clusters by evicting more compromised nodes from clusters. Last, our scheme saves the energy of nodes by employing broadcast communication. Simulation results prove that our scheme is more robust against compromised nodes and more energy-efficient than other scheme.

This paper deals with a pair-wise key establishment scheme without pre-distributing keys for ad-hoc networks. The scheme is based on the Diffie-Hellman key exchange protocol. It makes use of the one-time password to prevent a falsification of Diffie-Hellman values. Additionally, it forces each node to prove its long-term secret key ownership to provide mutual authentication. Security analyses prove that it is secure against various attacks. Also, simulation results show that it significantly reduces the number of messages to be exchanged over the probabilistic key pre-distribution scheme.

One of the most important issues affecting host mobility is the location and routing scheme that allows hosts to move seamlessly from one site to another. This paper presents a method that exploits the locality properties of a host's pattern of movement and access history. Two concepts, "local region" and "patron service" are introduced based on the locality features. For each mobile host, the local region is a set of designated subnetworks within which a mobile host often moves, and the patrons are the hosts from which the majority of traffic for the mobile host originated. These are used to confine the effects of a host moving, so location updates are sent only to its local area, and to those source hosts which are most likely to call again. Our scheme has the advantages of limiting location updates, and providing optimal routing, while increasing network and host scalability.>