NFV and SDN enable flexibility and programmability at the data plane. In addition, offloading packet processing to a hardware saves processing resources to compute other workloads. However, fulfilling requirements such as high throughput and low latency with a flexible and programmable data plane is challenging. This paper introduces eBPFlow, a platform for seamlessly accelerating network computation. It builds upon eBPF. eBPFlow combines flexibility and programmability in software with high performance using an FPGA. We implemented our system on the NetFPGA SUME, performing tests on a physical testbed. We built a range of NFs. Our results show that the eBPFlow supports offloading of NFs with throughput at the line rate, latency between$20~\mu \text{s}$and$40~\mu \text{s}$, communication with host, and consumption of 22 W. Moreover, eBPFlow processes 12.05 Mpps more than the kernel. eBPFlow has a throughput of 2.59 Gbps higher than the hXDP, a system similar to eBPFlow.

Underwater wireless acoustic networks (UWANs) take advantage of acoustic communication to enable many distinct applications. The peculiar features of underwater acoustic channels, such as long propagation delay, high bit error rates, and severely limited bandwidth, make the use of medium access control (MAC) solutions designed for terrestrial radio networks inefficient in UWANs. This paper proposes UW-SEEDEX, a MAC protocol for UWANs that employs random time slot schedules, created from seeds, to avoid collisions. After exchanging seeds, nodes can know other’s entire schedules, allowing them to then better plan their transmissions. Simulations evaluate how each of UW-SEEDEX’s parameter affects its performance in metrics such as end-to-end delay, energy consumption, transmissions per data reception, and reception rate using different test scenarios. Simulations also show that UW-SEEDEX can perform better than other MAC solutions, delivering more messages than protocols such as UW-Aloha and Slotted FAMA and reduced, on average, up to three times the number of transmissions required for each message reception in networks with grid topologies. UW-SEEDEX presented reception rates close to 100 percent, low energy cost, and fewer transmissions per data reception. Our code is available athttps://gitlab.com/epmcj/ns-3-dev/-/tree/new-uan-mac-protocols.

Core allocation for application threads is a problem of reasonable complexity and computational cost inside Unix systems. Caladan scheduler is a solution aiming to reduce the cost of how threads and cores are allocated in microsecond scale. The Danian system optimizes through memoization the thread picking algorithm that picks the best thread for a given core. Such improvements have direct impact on applications distributed across networks on a data center. Thread picking operation cost dropped from O(n) to O(1), the CPU time reduced 7%, the tail latency reduced 3% on Caladan Synthetic experiment and 5% on the Netperf experiment.

QUIC protocol is considered an experimental environment and a straight forward evolution of the TCP protocol. Applications created on top of QUIC demonstrate being more efficient than the regular HTTPS stack. Computational offload to kernel space is used as performance optimization for modern applications and brings with it a series of architectural and algorithmic challenges. This work presents eQUIC Gateway, a kernel space module that filter packets based on real time information exchanged with a user space QUIC application. Throughout kernel offload technique for filtering packets, eQUIC Gateway increased the packets throughput in 30.9%, reduced 65 % of the average HTTPS request duration under attack and reduced by 26.4% the CPU time consumed for filtering packets. The source code of eQUIC Gateway is public available on Github.

Circuit identification and classification is an important field of research in Electronic Design Automation (EDA). This paper provides a novel framework for circuit classification based on a Continuous Restricted Boltzmann Machine and Logistic Regression. An undirected graph representation of a circuit CNF instance is created and employed to perform CNF-signatures' search, thereof we classify it. A library with CNF-signatures of thousands of logic gates and functional blocks was pre-generated by our framework. These signatures are searched in the original CNF instance graph via traditional subgraph isomorphism algorithm and the results are applied as inputs for the Boltzmann Machine. Finally, a Logistic Regression classifier can determine to which class of the circuit each instance belongs. Our implementation is capable to correctly identify several circuit classes such as adders, multipliers and dividers with accuracy over 92%.

The use of two radios per node increases the energy efficiency of wireless sensor networks. Given that data collection is one of the most important functions in wireless sensor networks, this paper presents and compares two new data collection protocols for wireless sensor networks with two radios, DCTP-A and DCTP-I. DCTP-A builds the collection tree alternating the radio band each node while DCTP-I builds two independent collection trees. The protocols were implemented in TinyOS and evaluated experimentally in a testbed in the physical world using the 900MHz and 2.4GHz radio bands, compared to the state of the art (CTP and CTP-Multi) and to each other, considering the metrics delivery rate, latency, throughput in a saturated network scenario, total number of messages and the cost of maintaining routes. The results show the gain of the protocols for wireless sensor networks with two radios. DCTP-A achieved almost 100% of delivery rate, while DCTP-I achieved up to 90% delivery rate with less number of beacons messages.

In this work, we present Dribble a learn-based timer scheme selector to manage topology changes caused by mobility in the Internet of Things (IoT) context. IoT has turned smart devices part of our everyday lives. They are in everywhere with many shapes, sizes, and capabilities. For IoT to become even more ubiquitous, it is necessary to overcome the challenges posed by mobility. One of them is the management of topology changes, especially at the network layer. Currently, routing protocols check the topology through an advertisement timer scheme. Such schemes face a basic trade-off between being fast to find topology problems and concurrently be energy and overhead control saver. Although there are timer schemes designed to mobile context, all devices are governed by the same one, which is a hard assumption since IoT is heterogeneous and naturally, devices have different behaviors. Thus, Dribble learns the devices' mobility pattern and then it assigns a custom-made timer scheme conveniently for each device. Our results show that personalized timer schemes present better performance than single traditional timer schemes such as Trickle Timer (TT) and Reverse Trickle Timer (RevTT).

Recent advancements in underwater wireless sensor networks (UWSNs) are enabling day-one underwater monitoring applications. However, energy efficient and reliable UWSNs must be developed for achieving large scale and sustainable underwater monitoring and exploration applications. In this regard, the use of the underwater acoustic channel poses several daunting challenges. The acoustic channel is energy hungry and has low reliability, which shortens the UWSN lifetime and diminishes the performance of underwater monitoring applications. In the literature, both challenges have been addressed separately by means of duty-cycling and opportunistic routing, respectively. In this paper, we shed light on the symbiotic design of anypath routing and duty-cycling for sustainable UWSNs. We propose novel strobed preamble low power listening (LPL) and low power probing (LPP) methodologies for the design of asynchronous duty-cycling protocols, which symbiotically consider anypath routing for data delivery. Moreover, we develop an analytical framework for the performance evaluation of such a symbiotic design. Numerical results highlight potentials and drawbacks of this proposed approach in different classes of UWSN applications, and provide useful insights for the future symbiotic design of opportunistic routing and duty-cycling protocols for UWSNs.

Software Defined Vehicular Network (SDVN) is a new network architecture inspired by the well-known Vehicular Ad Hoc Network (VANET), applying the concepts of Software Defined Network (SDN). The SDVN proposes a complete data flow management by a module that controls the routing actions. However, it is necessary to verify that the security requirements are still satisfied. This paper presents Sentinel, a new defense mechanism to detect flooding attack by time series analysis of packet flow and mitigate the attack creating a flow tree to find out the source of spoofed packets. We divided the results between the detection rate of victim vehicles and the efficiency of mitigation method. The algorithm was able to mitigate the attack flow in different parameters. Sentinel reached an average mitigation rate of more than 78% in all densities scenarios.

Vehicular Networks represent an emerging technology that enables the use of network services by drivers and vehicle passengers. However, the heterogeneity of vehicular networks, which can use various wireless technologies, represents a challenge for the development of communication protocols. The Software Defined Vehicular Networks (SDVN) paradigm allows flexible design of these new protocols. This work proposes a new geocast protocol for Software Defined Vehicular Networks. Simulation results reveal that the proposed protocol outperforms the Inter- Vehicular Geocast protocol and the flooding algorithm in terms of delivery rate and signaling overhead.

Circuit structural recovering is a technique that derives functional blocks using low-level description. Its value resides chiefly in recovering information of high-level description from a project of integrated circuit when its design is lost, Intellectual Property (IP) synthesized in Field-Programmable Gate Array (FPGA), and in others cases when its structure is desirable. Furthermore, many SAT (Boolean satisfiability problem) solvers take advantage of information they can recover and knowledge of the domain problem to improve their processing (e.g. Algorithm Portfolios and Combinational Equivalence Checking). Being so, recovering circuit structural information is a key ingredient for improvements in formal verification using SAT solvers; a helpful step of structural recovering is the functional block identification. Taking an image generated from a circuit's CNF description, and considering CNN's maturity on the image recognition domain, we are able to map a macro functional block with a very high accuracy. The main contributions of this paper are the following: (i) We propose the innovative identification of functional blocks through images (ii) We implemented the system based on CNN using TensorFlow (iii) Our experimental results obtained an accuracy over 80%.

Monitoring underwater environments is still a hard and costly task. Indeed, electromagnetic and optical waves suffer high attenuation, being absorbed in a few meters and even acoustic communication presents low throughput and high bit error rate. Most of the existing approaches to enhance underwater communication performance relies on developing acoustic modems, multiple access to the communication channel and, data routing. In this paper, we present COPPER: a COoperative Protocol for PERvasive Underwater Acoustic Networks. COPPER synchronously/asynchronously works on top of TDMA method combined with an ARQ scheme based on selective repeat technique. It uses idle sensor nodes as relay nodes, enhancing communication space diversity. Our simulations show that, when compared to a non-cooperative protocol, COPPER enhances overall network performance metrics. For instance, it reduces packet error rate by 28.32% and increases goodput by 16.87% while spending less than 1% more energy.

Communications using wireless networks nowadays receives an increasing amount of users and devices. This implies in an increasing need for improvements in wireless networks. IEEE 802.11ac standard enables channels wider than 20 MHz bandwidth. But currently, access points allocate channel bandwidth statically, independent of the clients' configurations. This leads to poor network performance. In this work, we design a system that enables clients to choose the link's bandwidth they connect to the APs. We validate the system through realistic experiments. We show the trade-off between latency and throughput. Our results show that our system improves the frequency spectrum usage, and provide better throughput/latency for the user.

In this work, we argue that Location-Based Social Media (LBSM) feeds may offer a new layer to improve traffic and transit comprehension. Initially, we showed the significant correlation between Twitter's feed and traditional traffic sensors. Then, we presented the Twitter MAPS (T-MAPS) a low-cost spatiotemporal model to improve the description of traffic conditions through tweets. T-MAPS enhance traditional traffic sensors by carrying the human lens into the transportation system. We conducted a case study by running T-MAPS and Google Maps route recommendation, in which, we showed T-MAPS viability, as an additional traffic descriptor. As a result, we noticed the median of route similarity reached 62%, and for a quarter of the evaluated trajectories, the similarity achieved between 75% and 100%. Also, we presented three route description services, based on natural language analyzes, Route Sentiment (RS), Route Information (RI), and Area' Tags (AT) aiming to enhance the route information.

Many applications in Wireless Sensor Networks (WSNs) require collecting massive data in a coordinated approach. To that end, a many-to-one (convergecast) communication pattern is used in tree-based WSNs. However, traffic near the sink node usually becomes the network bottleneck. In this work, we propose an extension to the 802.15.4 standard for enabling wider bandwidth channels. Then, we measure the speed of data collection in a tree-based WSN, with radios operating in these wider bandwidth channels. Finally, we propose and implement Funneling Wider Bandwidth (FWB), an algorithm that minimizes schedule length in networks. We prove that the algorithm is optimal in regard to the number of time slots. In our simulations and experiments, we show that FWB achieves a higher average throughput and a smaller number of time slots. This new approach could be adapted for other relevant emerging standards, such as WirelessHART, ISA 100.11a and IEEE 802.15.4e TSCH.

It is estimated that Internet traffic will triple in five years, which will increase server response time. One way to reduce such time is to balance the load on replicated servers using SDN switches. However, existing SDN switches have performance limitations that influence the performance of the load balacing. This work compares five load balancing policies: round robin, random, txbytes (transmitted bytes), cpuq-load (CPU usage and number of open connections), and load/load-prev (load forecast with switch statistics). These policies consider limitations such as the cost to retrieve network statistics and to install new rules. The results show that the txbytes and cpuq-load policies outperformed the others. On the other hand, the load-prev policy proved to be promising when adjusted for traffic.

Wireless networks are very dynamic, having a variety of applications with different requirements. This diversity demands more flexible equipment as well as networks that adapt to the context of the applications. This work proposes FS-MAC, a platform that allows more than one MAC protocol to be used on the network. FS-MAC activates each of the MAC protocols when they are most effective. FS-MAC is also extensible, allowing the addition of new protocols. The proposal was tested in a testbed, where we varied the load and the number of connected stations. Results show that FS-MAC has throughput and delay values that are comparable to the best static protocol, having an overhead of around 2%.

Opportunistic routing (OR) has emerged as a promising paradigm to the design of routing protocols for underwater sensor networks (UWSNs). However, despite of its advantages, it introduces a critical problem that has been neglected until now: the immutable transmission priority level of the next-hop forwarding nodes. This characteristic can lead to an overuse of a unique node (or a few of them), quickly depleting its battery, creating network partitions, shortening the network lifetime and, consequently, degrading the application's performance. In this paper, we shed light on the need for mechanisms for rotating the forwarding priority level between candidate nodes. We propose a baseline new lightweight energy-aware opportunistic routing (EnOR) protocol, leading to a balanced energy consumption and prolonged UWSN network lifetime. EnOR rotates the transmission priority level of the forwarding candidate nodes by considering the remaining energy, link reliability and packet advancement of them. Simulation results reveal that EnOR effectively extends the network lifetime as compared with other underwater sensor network opportunistic routing protocols.

The decoupling of data and control planes of network switches is the main characteristic of Software Defined Networks. The OpenFlow (OF) protocol implements this concept and it is found today in various off-the-shelf equipment. Despite being widely employed in industry and research there is no systematic evaluation of OF data plane performance in the literature. In this paper we evaluate the performance and maturity of the main features of OF 1.0 on nine hardware and software switches. Results show that the performance varies significantly among implementations. For instance, packet delays vary by one order of magnitude among the evaluated switches, while the packet size does not impact the performance of OF switches.

Underwater networks are used for monitoring water resources and underwater environments. Thus, it is important that the underwater sensor nodes cover the largest region possible, during the largest amount of time. This paper presents a method to perform node scheduling in underwater stratified networks. It aims to maintain the network active for longer, maintaining its connectivity. Voronoi Diagrams are used to decompose the space into regions around each node in order to determine which one should be scheduled to sleep. Simulation results show that the proposed method achieves the desired objectives, more than doubling the network lifetime while guaranteeing connectivity.

Lately, there has been a growing interest in connecting opportunistic routing (OR) and low duty-cycling methodologies in underwater sensor network (UWSNs) applications. This connection improves the data collection reliability and prolongs the network lifetime. When sensor nodes operate in a duty-cycling manner, the properly sleep interval selection and its on-the-fly adjustment should be addressed. Both tasks are challenging when opportunistic routing protocols are used at the network layer, as they should consider the presence of the next-hop candidates set. In this paper, we propose a modeling framework to evaluate the effects of the sleep interval on the energy consumption of duty-cycled UWSNs, which employ opportunistic routing protocol at the network layer. We investigate the sleep interval control problem in the OR scenarios, formulating it as an optimization problem with the goal of extending the network lifetime. Our simulation results show that different fixed sleep interval duty-cycles do not impact on the average energy consumption whereas the sleep interval control can prolong the UWSN lifetime.

Power line communication systems face several challenges which degrade data communication quality. To overcome such issues, we propose CodePLC, a network coding Power Line Communication MAC protocol. We use a single relay node to intermediate communication, storing, and forwarding linear combinations of data packets. We evaluate CodePLC performance through simulations of a common topology for a PLC system under a wide range of scenarios. In sum, our results show that in a broadcast like transmission, the use of network coding enhances overall system performance. When compared to a traditional PLC system, we have observed an average of 115% goodput increase. Moreover, our protocol reduces in 112% the average of network occupancy buffers. Finally, CodePLC reduces mean latency by four times.

Many applications of sensor networks collect massive data in a coordinated approach, such as monitoring volcanoes, oceans and forests. We propose, therefore, two protocols at the network stack to enable multiple frequency communication. MultiFCTP extends the state-of-the-art CTP to route packets using multiples frequencies. FlushMF is a transport protocol that extends Flush by supporting multiple frequencies. FlushMF is a reliable transport protocol and high throughput for massive data. FlushMF provides end-to-end acknowledgment, reduces the transfer time, and adapts to network conditions that vary in time. A network system that uses multiple frequencies can be more robust to interference and achieve better throughput. Our study shows that FlushMF provides higher throughput than Flush.

In underwater sensor networks, the design of energy efficient and reliable data collection protocols is a daunting challenge. In this context, topology control and opportunistic routing are promising techniques for improving reliability and conserve energy. However, due to the challenges of the underwater acoustic channel, the vast knowledge acquired and the solution proposed so far in the context of terrestrial wireless ad hoc sensor networks cannot be applied directly to underwater acoustic sensor networks. In this work, we shed light on network topology modeling from a routing viewpoint. We model the probabilistic multipath routing behavior driven by opportunistic routing protocols in underwater sensor networks. Afterward, we propose the PCen centrality metric to measure the importance of underwater sensor nodes to the data delivery task through opportunistic routing protocols. PCen is aimed to identify critical nodes that can be used to guide topology control solutions. Our simulation results consider different network densities and reveal the presence of a few number of nodes with high PCen centrality value that will have a high rate of carried traffic, being critical for the network performance.

Standard routing protocols for IPv6 over Low power Wireless Personal Area Networks (6LoWPAN) are mainly designed for data collection applications and work by establishing a tree-based network topology, which enables packets to be sent upwards, from the leaves to the root, adapting to dynamics of low-power communication links. The routing tables in such unidirectional networks are very simple and small since each node just needs to maintain the address of its parent in the tree, providing the best-quality route at every moment. In this work, we propose Matrix, a platform-independent routing protocol that utilizes the existing tree structure of the network to enable reliable and efficient any-to-any data traffic. Matrix uses hierarchical IPv6 address assignment in order to optimize routing table size, while preserving bidirectional routing. Moreover, it uses a local broadcast mechanism to forward messages to the right subtree when persistent node or link failures occur. We implemented Matrix on TinyOS and evaluated its performance both analytically and through simulations on TOSSIM. Our results show that the proposed protocol is superior to available protocols for 6LoWPAN, when it comes to any-to-any data communication, in terms of reliability, message efficiency, and memory footprint.

Underwater wireless sensor networks (UWSNs) have been showed as a promising technology to monitor and explore the oceans in lieu of traditional undersea wireline instruments. Nevertheless, the data gathering of UWSNs is still severely limited because of the acoustic channel communication characteristics. One way to improve the data collection in UWSNs is through the design of routing protocols considering the unique characteristics of the underwater acoustic communication and the highly dynamic network topology. In this paper, we propose the GEDAR routing protocol for UWSNs. GEDAR is an anycast, geographic and opportunistic routing protocol that routes data packets from sensor nodes to multiple sonobuoys (sinks) at the sea's surface. When the node is in a communication void region, GEDAR switches to the recovery mode procedure which is based on topology control through the depth adjustment of the void nodes, instead of the traditional approaches using control messages to discover and maintain routing paths along void regions. Simulation results show that GEDAR significantly improves the network performance when compared with the baseline solutions, even in hard and difficult mobile scenarios of very sparse and very dense networks and for high network traffic loads.

The problem of reliable data delivery at low energy cost arises as one of the most challenging research topics in underwater wireless sensor networks (UWSNs). Reliable data delivery is demanding because of the acoustic channel impairments and channel fading. Moreover, it is energy hungry given the high cost of acoustic communication. In wireless ad hoc & sensor networks, separately, opportunistic routing has been employed to improve data delivery whereas duty cycled operation mode has been adopted to achieve energy efficiency and prolonging network lifetime. In this paper, we investigate the benefits and drawbacks of collision between opportunistic routing paradigm and duty cycle techniques in UWSNs. We propose an analytical model to study and evaluate the performance of opportunistic routing protocols under duty cycled settings designed from three mainly paradigms: simple asynchronous, strobed preamble and receiver initiated; and different network densities and traffic loads. The results show that while duty cycle reduces the energy consumption, it affects negatively in the opportunistic routing performance, increasing the delay and the expected number of transmissions to deliver a packet. The simple duty cycled approach is shown to be suitable for applications that require long-lived network and can tolerate some degree of packet losses. Our results indicate that strobed preamble-based duty cycle is the most effective approach to be integrated with opportunistic routing, when high fidelity monitoring is required, even having not the best performance in terms of energy savings.

In this work, we propose eXtend Collection Tree Protocol (XCTP), a routing protocol that is an extension of the Collection Tree Protocol (CTP). CTP is the de-facto standard collection routing protocol for Wireless Sensor Network (WSN). CTP creates a routing tree to transfer data from one or more sensors to a root (sink) node. But, CTP does not create the reverse path between the root node and sensor nodes. This reverse path is important, for example, for feedback commands or acknowledgment packets. XCTP enables communication in both ways: root to node and node to root. XCTP accomplishes this task by exploring the CTP control plane packets. XCTP requires low storage states and very low additional overhead in packets. With the reverse path, it is possible to implement reliable transport layer protocols for Wireless Sensor Network (WSN). Thus, we designed Transport Automatic Piggyback Protocol (TAP2), a transport protocol with Automatic Repeat-reQuest (ARQ) error-control on top of XCTP. We implemented these protocols on TinyOS and evaluated on TOSSIM. We compared XCTP with CTP, Routing Protocol for low-power and lossy networks (RPL), and Ad hoc On Demand Distance Vector (AODV) protocols. We conducted scalability and stress tests, evaluating them with different loads and number of nodes. Our results shows that XCTP is more reliable than CTP, delivering 100% of the packets. XCTP sends fewer control packets than RPL. XCTP is faster to recovery from network failures and also stores fewer states than AODV, thus being efficient and agile.

Efficient protocols for data packet delivery in mobile underwater sensor networks (UWSNs) are crucial to the effective use of this new powerful technology for monitoring lakes, rivers, seas, and oceans. However, communication in UWSNs is a challenging task because of the characteristics of the acoustic channel. In this work, we present a feasible solution for improving the data packet delivery ratio in mobile UWSN. The GEographic and opportunistic routing with Depth Adjustment-based topology control for communication Recovery (GEDAR) over void regions uses the greedy opportunistic forwarding to route packets and to move void nodes to new depths to adjust the topology. Simulation results shown that GEDAR outperforms the baseline solutions in terms of packet delivery ratio, latency and energy per message.

Local maximum problem, where the node fails in determine the next-hop neighbor to continue forwarding the packet towards the destination, severely degrades the performance of geographic routing protocols. This degradation is more substantial in underwater sensor networks, that intrinsically have harsh environments and high energy consumption due to the underwater acoustic communication characteristics. In this work, we focus on the performance of the most commonly three methodologies used in design of local maximum recovery procedures of geographic routing protocols for underwater sensor networks: power control, bypassing void regions, and mobility controlled. Taking into consideration the underwater acoustic communication characteristics, we further develop a network energy consumption model for representative solutions of local maximum recovery procedure designed from these methodologies and then we evaluate their performance in terms of the improvements on routing task and the energy consumption. Simulation results show that all three methodologies improve the routing even in hard scenarios of lower network density whereas particularities of each methodology impacts on the network energy consumption.

Energy efficient and reliable communication are two very important and conflicting requirements in the design of large-scale, self-organizing wireless sensor networks (WSNs). By reducing the transmission power level of the nodes, energy conservation is achieved whereas the communication reliability is degraded. We propose a novel opportunistic routing protocol to reduce the energy consumption while keep the communication reliability in acceptable levels. Transmission power Control-based Opportunistic Routing (TCOR) saves energy by reducing the transmission power of the nodes while maintains the communication reliability by employing the opportunistic forwarding paradigm, leveraging the broadcast nature of wireless transmission medium. We propose an expected energy cost function for next-hop forwarder set selection, which considers the multiple available transmission power levels and the impact of each one on the next-hop packet reception probability.

Localization is a paramount concern in wireless sensor networks. Beacon nodes, which have their position defined a priori, might be used in the process, serving as references to find the position of other nodes. Many studies focused on finding the location of as many nodes as possible, given a set of beacons and distance measurements. In this work, we determine the set of beacon nodes in order to localize all nodes in the network. This can reduce the overall cost involved in the network localization process, i.e., reducing the number of nodes in a WSN with GSP. We present a new approach to this problem using Genetic Algorithms. Our simulations results show the efficiency of the proposed approach, which has results up to 50% better than the best greedy algorithm found in the literature.

Underwater sensor networks have recently been proposed as a way to observe and explore the lakes, rives, seas, and oceans. However, due to characteristics of the acoustic medium, efficient protocols for delivering data must exist. In this work, we propose a novel geographic routing protocol with network topology control for underwater sensor networks, that adjusts the depth of the nodes in order to organize the network topology for improving the network connectivity and forward data where the greedy geographic routing fail. The proposed protocol is the first geographic routing protocol for underwater sensor networks that considers the sensor node vertical movement ability to move it for topology control purpose. The simulation results show that, with the topology control, the fraction of disconnected nodes and nodes located into communication void regions, are drastically reduced and consequently the delivered data rate is improved. It achieves more than 90% of data delivered even in hard and difficult scenarios of very sparse or very dense networks.

Under-Water Wireless Sensor Networks (UWSNs) are a particular class of Wireless Sensor Networks (WSNs) in which sensors are located, as the name suggests, underwater. Applications of UWSNs range from oceanographic data collection to disaster prevention. UWSNs are vulnerable to attacks and because of their idiosyncrasies, security solutions for ground WSNs might not be applicable underwater. As a result, there is a need for mechanisms exclusively tailored to underwater environments. In this work we address the problem of authentication in UWSNs. We evaluate energy costs for different digital signature schemes for end-to-end authentication and discuss the tradeoffs involved in a number of scenarios. Our results show that schemes that perform well in ground WSN do not necessarily do well in UWSNs; and shed light on characteristics of a digital signature scheme that make them particularly suited to underwater networks.

Underwater sensor networks have recently been proposed as a way to observe and to explore the lakes, rivers, seas, and oceans. A challenging issue in these networks is the communication, mainly due to the impairments of the acoustic transmission. Thus, efficient mechanisms to improve the data delivery must be proposed. In this work we present a novel anycast greedy geographic forwarding protocol and two topology control mechanisms. The proposed geo-routing protocol considers the anycast network architecture in the data forwarding process. The proposed centralized topology control (CTC) and distributed topology control (DTC) mechanisms organize the network via depth adjustment of some nodes. The simulation results show that with these mechanisms, the data packet delivery ratio achieves more than 90% even in hard and difficult scenarios of very sparse or very dense networks, the end-to-end delay and energy consumption per delivered packet is reduced.

Despite great effort from the research community, wireless networks still operate below full capacity. To increase the network throughput it is important to study algorithms that select communication requests that can decode their signals despite mutual interference. In this paper, we study the joint problem of data rate assignment and link scheduling in the physical interference model. The objective of the problem is to maximize the total number of bits transmitted in one time slot. By constructing an intermediate network representation through a disk graph, we prove that a constant approximation solution can be computed in polynomial time. Finally, we propose a parallel implementation of a polynomial-time approximation scheme and show through simulations that the one-slot throughput of a wireless network can be significantly improved by using variable data rates.

Future wireless Internet envisions that thousands of embedded devices will be integrated to the Internet. These devices, which can be micro-controllers with radio and sensor components, require communication protocols to establish a network. But, some embedded devices have scarce RAM resource. Our work shows that it is possible to implement an IPv6 stack over Low power Wireless Personal Area Networks (6LowPAN) for RAM constrained systems. We are able to implement the RPL routing protocol with less than 512 bytes of RAM. To handle the hard RAM constraint, we develop a circular queue and a swap content mechanism from RAM to Flash memory. We develop a platform and tested the implementation with realist experiments. Our research has the potential for a great impact since it enables interconnecting many lower cost devices to the Internet.

We present NanoRouter, a new router architecture implemented as a quantum-dot cellular automata (QCA). A router is a key component in the Internet core. It allows packets to be transferred in the Internet. QCA is a promising nanoscale technology where components have nano size, ultra-low power consumption and could have a clock rate on the terahertz range. In a bottom-up approach, we first describe the building blocks that compose NanoRouter such as crossbar, demux and parallel-to-serial converter and then describe the full architecture. We demonstrate the functionality, test and validate the proposed architecture and provided performance evaluations of NanoRouter. This new router architecture can increase the speed of the Internet core.

In this paper we present a new routing paradigm for wireless multihop networks. In plasma routing, each packet is delivered over the best available path to one of the gateways. The choice of the path and gateway for each packet is not made beforehand by the source node, but rather on-the-fly by the mesh routers as the packet traverses the network. We propose a distributed routing algorithm to jointly optimize the transmission rate and the set of gateways each node should use. A load balancing technique is also proposed to disperse the network traffic among multiple gateways. We validate our proposal with simulations and show that plasma routing outperforms the state-of-the-art multirate anypath routing paradigm, with a 98% throughput gain and a 2.2x delay decrease. Finally, we also show that the load can be evenly distributed among gateways with a similar routing cost, resulting in a further 63% throughput gain.

Wireless communication technology offers multi-rate transmission capability which allows to increase the network's throughput. Nevertheless, previous algorithmic results have focused on single-rate radios. In this paper, we study the problem of scheduling multi-rate wireless requests considering the physical interference model. The objective of the problem is to select a subset of communication requests such that the sum of their data rates is maximized and no collisions occur if they are all scheduled simultaneously. We show that, under certain constraints on the input, the problem can be approximated by a graph-based model. More specifically, if network nodes live in a two-dimensional Euclidean space, where the path loss exponent is strictly larger than two, and if data rates and sender-receiver distances can only differ by a contact factor between communication requests, the problem can be modeled as a disk graph. This means that, despite the global nature of the physical interference model, conflicts between simultaneous requests can be restricted to the local neighborhood of the transmitting nodes. We show how to build the corresponding disk graph instances and prove that a weighted maximum independent set in this graph-based model provides a constant-factor approximation to the multi-rate scheduling problem in the physical interference model. Moreover, we implement a polynomial-time approximation scheme algorithm to obtain solutions that are within an arbitrarily small factor of being optimal in the disk graph model.

The research of underwater sensor networks (UWSNs) is gaining attention due to its possible applications in many scenarios, such as ecosystem preservation, disaster prevention, oil and gas exploration and freshwater reservoirs management. The main elements of a UWSN are underwater sensor nodes (UWNs). In this paper we present HydroNode: a low cost, energy efficient, multipurpose underwater sensor node (UWN). Nowadays, to the best of our knowledge, there is no UWNs that is simultaneously low cost, low power, able to couple diverse types of sensors and educationally available. Thus, the objective of this paper is to fill this gap by describing the design of HydroNode, an underwater sensor node that fulfill all these requirements and can be used in various UWSNs applications. We used only commercial off-the-shelf components to build our underwater sensor node. Due to its multipurpose design, HydroNode can be used in different UWSNs, therefore aiding the research of UWSN system protocols, configurations and applications.

Underwater acoustic channel imposes many challenges into underwater networks communication, such as high bit error, temporary losses of connectivity due to shadow zones, limited bandwidth capacity and communication signal spreading over large areas. Opportunistic routing is a new routing paradigm that allows more than one node to forward a packet by taking advantage of the broadcast medium and overhearing of the packet transmission. In this paper we investigate the tradeoffs present in opportunistic routing for underwater networks. In one hand opportunistic routing may increase the time it takes to receive a packet, since there is an increase in delay to allow all the nodes that are possible forwards to receive the packet. On the other hand, opportunistic routing can help mitigated underwater challenges, by providing gain in packet reception and channel utilization. We provided an analysis of underwater channel utilization efficiency in opportunistic routing. We evaluated the performance on random deployments, showing that by using opportunistic routing we have a gain in packet reception and channel utilization in underwater networks.

Localizing a user is a fundamental problem that arises in many potential applications. The use of wireless technologies for locating a user has been a trend in recent years. Most existing approaches use RSSI to localize the user. In general, one of the several existing wireless standards such as ZigBee, Bluetooth or Wi-Fi, is chosen as the target standard. An interesting question that has practical implications is whether there is any benefit in using more than one wireless technology to perform the localization. In this paper we present a study on the advantages and challenges of using multiple wireless technologies to perform localization in indoor environments. We use real ZigBee, Wi-Fi and Bluetooth compliant devices. In our study we analyse results obtained using the fingerprint method. The performance of each technology alone and the performance of the technologies combined are also investigated. We also analyse how the number of wireless devices used affects the quality of localization and show that, for all technologies, more beacons lead to less error. Finally, we show how interference among technologies may lead to lower localization accuracy.

Underwater Sensor Networks (UWSNs) and Aeronautical Ad Hoc Networks (AANETs) are Mobile Ad Hoc Networks (MANETs) that need to consider the 3D nature of the network. UWSN presents the opportunity for many applications such as coast surveillance, and 4D monitoring (space and time) for ocean and biology studies. In AANET, aircrafts can communicate among each other and enhance situation awareness. In this work we study the fundamental properties of 3D MANETs: Link Probability, Node Degree and Network Coverage. This work was motivated by fundamental problems currently faced in the deployment of underwater sensor networks and aeronautical ad hoc networks. Link Probability is important in MAC protocols development. Determining network coverage is important for sensing applications, i.e., how to guarantee sensing coverage. Node degree is useful in scheduling duty cycles. Since energy is a limited resource, utilizing duty cycles is a major technique to improve network lifetime. We present analytical results for link probability, node degree and network coverage for 3D MANETs assuming random uniform distribution. These results may be applied to a variety of scenarios, platforms and applications. In addition, we describe applications that would benefit from our results.

A SEA Swarm (Sensor Equipped Aquatic Swarm) is a sensor "cloud" that drifts with water currents and enables 4D (space and time) monitoring of local underwater events such as contaminants, marine life and intruders. The swarm is escorted at the surface by drifting sonobuoys that collect the data from underwater sensors via acoustic modems and report it in real-time via radio to a monitoring center. The goal of this study is to design an efficient anycast routing algorithm for reliable underwater sensor event reporting to any one of the surface sonobuoys. Major challenges are the ocean current and the limited resources (bandwidth and energy). In this paper, we address these challenges and propose HydroCast, a hydraulic pressure based anycast routing protocol that exploits the measured pressure levels to route data to surface buoys. The paper makes the following contributions: a novel opportunistic routing mechanism to select the subset of forwarders that maximizes greedy progress yet limiting co-channel interference; and an efficient underwater "dead end" recovery method that outperforms recently proposed approaches. The proposed routing protocols are validated via extensive simulations.

A SEA Swarm (Sensor Equipped Aquatic Swarm) is a collection of mobile underwater sensors that moves as a group with water current and enables 4D (space and time) monitoring of local underwater events such as contaminants and intruders. For prompt alert reporting, mobile sensors routes events to mobile sinks (i.e., autonomous underwater vehicles) via geographic routing that is known to be most efficient under mobility and scarce acoustic bandwidth. In order for a packet to be routed to the destination using geographical routing, it requires to know the location of the destination. This is accomplished by having a location service that returns the location of a requested node. Our goal is to design such location service for SEA Swarm. In this paper, we analyze various design choices to realize an efficient location service in SEA Swarm scenarios. We find that conventional ad hoc network location service protocols cannot be directly used, because the entire swarm moves along water current. We prove that maintaining location information in a 2D plane is a better design choice. Given this, we propose a bio-inspired location service called a Phero-Trail location service protocol. In Phero-Trail, location information is stored in a 2D upper hull of a SEA Swarm, and a mobile sink uses its trajectory (a la a pheromone trail of ants) projected to the 2D hull to maintain location information. This enables mobile sensors to efficiently locate a mobile sink. Our results show that Phero- Trail performs better than existing approaches.

Biochemical activities in sewer pipes generate various volatile substances that lead to several serious problems such as malodor complaints and lawsuits, concrete and metal corrosion, increased operational costs, and health risks. Frequent inspections are critical to maintain sewer health, yet are extremely expensive given the extent of the sewer system and the "unfriendliness" of the environment. In this paper we propose SewerSnort, a low cost, unmanned, fully automated in-sewer gas monitoring system. A sensor float is introduced at the upstream station and drifts to the end pumping station, collecting location tagged gas measurements. The retrieved SewerSnort provides an accurate gas exposure profile to be used for preventive maintenance and/or repair. The key innovations of SewerSnort are the fully automated, end-to-end monitoring solution and the low energy self localizing strategy. From the implementation standpoint, the key enablers are the float mechanical design that fits the sewer constraints and the embedded sensor design that matches the float form factor and complies with the tight energy constraints. Experiments based on a dry land emulator demonstrate the feasibility of the SewerSnort concept, in particular, the localization technique and the embedded sensor design.

Underwater mobile acoustic sensor networks are promising tools for the exploration of the oceans. These networks require new robust solutions for fundamental issues such as: localization service for data tagging and networking protocols for communication. All these tasks are closely related with connectivity, coverage and deployment of the network. A realistic mobility model that can capture the physical movement of the sensor nodes with ocean currents gives better understanding on the above problems. In this paper, we propose a novel physically-inspired mobility model which is representative of underwater environments. We study how the model affects a range-based localization protocol, and its impact on the coverage and connectivity of the network under different deployment scenarios.

Language Emulator, written in Java, is a toolkit to help undergraduate students to understand the concepts of Automata Theory. The software allows the manipulation of regular expressions, regular grammars, deterministic finite automata, nondeterministic finite automata with and without lambda transitions, and Moore and Mealy machines. Language Emulator introduces error-detecting and internationalization functionalities into automata tools. It has been accepted by 95% of students in a recent survey, indicating that it is a helpful toolkit in learning Automata Theory.

Power consumption became a crucial problem in the development of mobile devices, especially those that are communication intensive. In these devices, it is imperative to reduce the power consumption devoted to maintaining a communication link during data transmission/reception. The application of dynamic power management methodologies has contributed to the reduction of power consumption in general purpose computer systems. However, to further reduce power consumption in communication intensive real-time embedded devices, we have to consider the state of the computation and external events in addition to power management policies. In this paper we propose a model of an Extended Power State Machine (EPSM), where we adapt a Power State Machine to include the state of an embedded program in the power state machine formulation. This EPSM model is used to adapt the Quality of Service (QoS) in communication intensive devices to ensure low power consumption. In such development, a middleware layer fits in the system's architecture, being responsible for intercepting the data communication and implementing the EPSM. Also, a software tool was developed, allowing the Middleware Code to be generated based on the State Machine. A case study demonstrates the application of the proposed model to a real situation.

A wireless sensor network is a special kind of ad-hoc network with distributed sensing and processing capability that can be used in a wide range of applications, such as environmental monitoring, industrial applications and precision agriculture. Despite their potential applications, such networks have particular features imposed by resource restrictions, such as low computational power, reduced bandwidth and specially limited power source. In case of a network with a high density of sensor nodes, some problems may arise such as the intersection of sensing area, redundant data, communication interference, and energy waste. A management application is necessary to make the most of network resources. On the other hand, a high-density network can introduce a fault-tolerant mechanism, increase precision, and provide multi-resolution data. The network density control depends on the application. In this paper, we propose a method to set up which nodes should be turned off or on. The management may take the sensor node out of service temporally. Our design uses a Voronoi diagram, which decomposes the space into regions around each node. That schema could be used in management architecture for a wireless sensor network.