Military communities have come to rely heavily on commercial off the shelf (COTS) standards and technologies for Internet of Things (IoT) operations. One of the major obstacles to military use of COTS IoT devices is the security of data transfer. In this paper, we successfully design and develop a lightweight, trust-based security architecture to support routing in a mobile IoT network. Specifically, we modify the RPL IoT routing algorithm using common security techniques, including a nonce identity value, timestamp, and network whitelist. Our approach allows RPL to select a routing path over a mobile IoT wireless network based on a computed node trust value and average received signal strength indicator (ARSSI) value across network members. We conducted simulations using the Cooja network simulator and Wireshark to validate the algorithm against stipulated threat models. We demonstrate that our algorithm can protect the network against Denial of Service (DoS) and Sybil based identity attacks. We also show that the control overhead required for our algorithm is less than 5% and that the packet delivery rate improves by nearly 10%.

Recently, demands for low-power wide-area (LPWA) machine-type communications have increased dramatically. It is expected that LPWA connections will reach 2 billion in 2020, exceeding the number of traditional cellular users. Narrowband Internet of Things (NB-IoT), a new radio access technology, has been released by the Third Generation Partnership Project for such demands. NB-IoT supports super coverage extension, massive number of connections and long user lifetime with low power cost and low device complexity. With such prominent features, NB-IoT has become one of the dominating technologies in LPWA networks, applicable to a large range of IoT application scenarios such as smart meter, smart parking, smart home, smart tracking, e-health, etc. However, NB-loT is still in its infancy, needing deep theoretical investigation of modeling and optimizing system performance. Also, emerging applications that can be enabled by NB-loT and implementation challenges therein need further exploration.

Large Unmanned Aerial Vehicle (UAV) swarms are a nascent technology promising useful military and civilian solutions to logistical problems. Securing data communications within the swarm is essential to accomplishing swarm objectives. The Naval Postgraduate School has successfully demonstrated the launch, flight and landing of 50 UAVs. The communications architecture to support a UAV swarm is unique. This paper details the practical challenges of creating a secure communications channel in the swarm. The Advanced Encryption Standard (AES) was chosen as one of the encryption algorithms for testing as it is authorized by the National Security Agency (NSA). Various modes of AES, including Galois/Counter Mode (GCM) and Counter with Cipher Block Chaining Message Authentication Code (CCM), were analyzed within the swarm architecture. The impact of these authenticated encryption algorithms on network capacity and processor performance is presented. In addition to AES, ChaCha20-Poly1305, another type of authenticated encryption scheme was studied. It was found to be the better solution for securing the swarm if classified data is not being handled or created.

The IETF is developing an IPv6 Routing Protocol for Low Power and Lossy Networks (RPL) for smart machine-to-machine networks. In this paper, we present a RPL protocol for the mesh based multigateway Advanced Metering Infrastructure (AMI) of the Smart Grid. The multigateway RPL is based on the construction and maintenance of multiple directed acyclic graphs (DAG) that are each rooted at a gateway. The DAGs are constructed using node rank computation. We incorporate an interference based routing metric into the RPL to facilitate rank computation. The interference link metric, based on SINR measurements, is used to construct and maintain DAGs for least interference routing. We will show that our multigateway RPL protocol performs better in terms of packet delivery ratio, delay and throughput when compared to generic routing schemes such as AODV and RPL protocols that use ETX (expected transmission time) as the link metric. We also study the multigateway RPL under link failures to show that high throughput data routing can be achieved.

In this paper, we investigate the problem of flow routing and fair bandwidth allocation under interference constraints for multihop wireless networks. We first develop a novel isotonic routing metric, RI3M, considering the influence of interflow and intraflow interference. The isotonicity of the routing metric is proved using virtual network decomposition. Second, in order to ensure QoS, an interference-aware max-min fair bandwidth allocation algorithm, LMX:M3F, is proposed where multiple paths (determined by using the routing metric) coexist for each user to the base station. In order to solve the algorithm, we develop an optimization formulation that is modeled as a multicommodity flow problem where the lexicographically largest bandwidth allocation vector is found among all optimal allocation vectors while considering constraints of interference on the flows. We compare our RI3M routing metric and LMX:M3F bandwidth allocation algorithm with various interference-based routing metrics and interference-aware bandwidth allocation algorithms established in the literature. We show that RI3M and LMX:M3F succeed in improving network performance in terms of delay, packet loss ratio, and bandwidth usage.

Fairness and system throughput, influenced by wireless interference, are major objectives of resource allocation in wireless networks. Whereas traditionally max-min fairness protocols have been developed for wired networks (where interference is not a factor for network performance), in this paper we investigate the problem of flow routing and fair bandwidth allocation under the constraints of the physical interference model for multihop wireless networks. A max-min fair (MMF) routing algorithm under physical interference constraints is proposed where multiple candidate paths coexist for each user to the base station. The algorithm is formulated as a multicommodity flow problem where the lexicographically largest bandwidth allocation vector is found among all optimal allocation vectors. We compare our approach with two MMF interference routing algorithms in the literature that use the protocol interference model to garner fair bandwidth allocation. We show that our algorithm performs better in terms of blocking probability, bandwidth usage and link load.

This paper addresses the problem of discovering least interfering paths in the context of multipath routing in multihop wireless networks using the SINR based interference model. Whereas traditionally interference has been quantified using the protocol model, we propose a disjoint multipath interference aware routing algorithm, known as DMPR:SINR, using a weighted SINR conflict graph to quantify interference. In addition, to ensure QoS, bandwidth and path flow restoration is implemented on the secondary routing path using an optimization formulation if a link failure occurs on the primary routing path. We compare our algorithms with disjoint multipath routing protocols in the literature that 1) considers interference using a version of the protocol model and 2) considers interference induced by the SINR model within a restricted range. We show that our algorithms outperform established disjoint multipath routing protocols in terms of normalized throughput, end-to-end delay and bandwidth usage.

In this paper, we formulate a flow control optimization problem for wireless sensor networks with lifetime constraint and link interference in an asynchronous setting. Our formulation is based on the network utility maximization framework, in which a general utility function is used to characterize the network performance such as throughput. To solve the problem, we propose a fully asynchronous distributed algorithm based on dual decomposition, and theoretically prove its convergence. The proposed algorithm can achieve the maximum utility. Extensive simulations are conducted to demonstrate the efficiency of our algorithm and validate the analytical results.

In the paper, we study the utility-lifetime tradeoff in wireless sensor networks (WSNs) by formulating it as a constrained multi-objective optimization problem. Because of the coupling in the objective function, auxiliary variables are introduced to decouple it. We adopt Lagrange duality method to decompose the problem and regulate the rates through the link congestion price. We introduce the concept of inconsistent coordination price to balance the energy consumption of the sensor nodes. Based on the congestion and inconsistent coordination price, a distributed algorithm using gradient projection is proposed. Numerical results show the convergence of our algorithm, the tradeoff of utility-lifetime as well as the necessity of congestion control in WSNs.

The wireless relay mesh network (WRMN) is designed to provide robust and fault tolerant communications between relay and user nodes in broadband wireless networks. In this paper, we study interference aware resource allocation in OFDMA based WRMNs and the effects of spatial reuse on throughput. We propose an interference aware subcarrier assignment (IASA) algorithm to allocate subcarriers to links in the network such that interference is mitigated and throughput is maximized. The protocol interference model and spatial reuse are exploited to achieve the subcarrier assignment. We show that our IASA algorithm improves throughput compared to when subcarriers are used only once. However, overuse of a single subcarrier can have detrimental effects on network performance, therefore a balance must be achieved. In addition, using a maximum concurrent flow (MCF) approach, we show that under the IASA scheme of spatial reuse, throughput can be enhanced. We formulate the MCF as a linear program and solve it using dual optimization techniques. We compare our proposed algorithm with that of a graph coloring approach using a conflict graph and column generation to show that our throughput results are better than those obtained by the link coloring strategy.

Wireless sensor networks (WSN) are typically employed for monitoring applications that require data collection at specific nodes, called drains. In order to improve the robustness of data collection, multiple drains may be employed. Data from every sensor is required to be logged into two distinct sensors for data collection to be resilient to any single drain failures. In this paper, we develop a routing mechanism based on colored trees. Every node forwards the packets based on the drain address and one additional bit. The number of routing table entries at each node is 2|D|, where |D| denotes the number of drains in the network. The construction of the colored trees guarantees that every node has two node-disjoint paths to two distinct drains. The running time complexity of the algorithm is O(|D||L|), where |L| denotes the number of links in the network. Through extensive simulations, we demonstrate that employing multiple drains and disjoint routing to two distinct drains reduces the average path length compared to disjoint routing to one of the multiple drains.

Wireless sensor networks (WSNs) employed in monitoring applications require data collected by the sensors to be deposited at specific nodes, referred to as drains. To improve robustness in data collection, we consider a dual homing network in which two drains are employed and every node is required to send data to the two drains over link- or node-disjoint paths. One approach to reduce the number of routing table entries at a node is to construct two trees, namely red and blue, each rooted at a particular drain such that the paths from any node to the two drains on the trees are link- or node-disjoint. In this paper, we develop the first distributed algorithm for constructing colored trees in a dual-homing network whose running time is linear in the number of links. In addition, we show that the average path length may be optimized by employing the generalized low-point concept rather than the traditional low-point concept.