Due to the lossy nature of wireless links, it is difficult to determine if packet losses are due to wireless-induced effects or from malicious discarding. Many prior efforts on detecting malicious packet drops rely on evidence collected via passive monitoring by neighbor nodes. However, they do not analyze the cause of packet losses. In this paper, we ask: 1) Given certain macroscopic parameters of the network (like traffic intensity and node density) what is the likelihood that evidence exists with respect to a transmission? 2) How can these parameters be used to perform a forensic analysis of the reason for the losses? Toward answering the above questions, we first build an analytical framework that computes the likelihood that evidence (we call this transmission evidence, or TE for short) exists with respect to transmissions, in terms of a set of network parameters. We validate our analytical framework via both simulations as well as real-world experiments on two different wireless testbeds. The analytical framework is then used as a basis for a protocol within a forensic analyzer to assess the cause of packet losses and determine the likelihood of forwarding misbehaviors. Through simulations, we find that our assessments are close to the ground truth in all examined cases, with an average deviation of 2.3% from the ground truth and a worst case deviation of 15.0%.

Transmission Evidence (TE for short) refers to a historic trail of the packet transmissions in the network. TE is collected and maintained in a distributed manner by the nodes in the network and can be queried on demand by a network forensics system to trace past events. The latter can facilitate crucial applications such as identifying malicious or malfunctioning nodes. Recently, we developed an analytical framework towards computing the likelihood of TE availability in wireless networks. Our prior efforts [1] brought to light the impact of the network's operational parameters (such as transmission rate and packet length) on the availability of TE. However, provisioning for TE could impact the network performance in terms of throughput and/or delay. Our objective in this work is to capture and quantify the trade-offs between provisioning transmission evidence and achieving high performance in wireless networks. In particular, we investigate the network performance hit, under the constraint of TE availability guarantees. Our results indicate that the performance remains unaffected up to a certain TE requirement. Beyond this, the throughput could degrade and the delay could increase by as much as 30%. To the best of our knowledge, this is the first study of its kind.

In multiuser multiple-input-multiple-output (MIMO) networks, receivers decode multiple concurrent signals using successive interference cancellation (SIC). With SIC, a weak target signal can be deciphered in the presence of stronger interfering signals. However, this is only feasible if each strong interfering signal satisfies a signal-to-noise-plus-interference ratio (SINR) requirement. This necessitates the appropriate selection of a subset of links that can be concurrently active in each receiver's neighborhood; in other words, a subtopology consisting of links that can be simultaneously active in the network is to be formed. If the selected subtopologies are of small size, the delay between the transmission opportunities on a link increases. Thus, care should be taken to form a limited number of subtopologies. We find that the problem of constructing the minimum number of subtopologies such that SIC decoding is successful with a desired probability threshold is NP-hard. Given this, we propose MUSIC, a framework that greedily forms and activates subtopologies in a way that favors successful SIC decoding with a high probability. MUSIC also ensures that the number of selected subtopologies is kept small. We provide both a centralized and a distributed version of our framework. We prove that our centralized version approximates the optimal solution for the considered problem. We also perform extensive simulations to demonstrate that: 1) MUSIC forms a small number of subtopologies that enable efficient SIC operations; the number of subtopologies formed is at most 17% larger than the optimum number of topologies, discovered through exhaustive search (in small networks); 2) MUSIC outperforms approaches that simply consider the number of antennas as a measure for determining the links that can be simultaneously active. Specifically, MUSIC provides throughput improvements of up to four times, as compared to such an approach, in various topological settings. The improvements can be directly attributable to a significantly higher probability of correct SIC based decoding with MUSIC.

While network coding can potentially provide significant throughput benefits by combining packets prior to forwarding them, the achievable gains are directly related to the coding opportunities at a relay that performs encoding. If the relay does not have packets destined for distinct destinations, that can be encoded together, the network coding gains could be marginal. Towards increasing the opportunities for network coding, in this paper we propose a queue management scheme, that arbitrates the rate at which distinct transmitters send packets to a common relay which applies network coding. Our queue management approach prioritizes the channel access of nodes that do not have enough enqueued packets at the common relay, thereby essentially attempting to balance the number of packets from the distinct senders at the relay. We perform extensive simulations of our approach (built as a wrapper on top of the popular network coding approach COPE) in multi-rate scenarios. We find that our approach yields throughput gains of up to 57% compared to COPE due to enhanced opportunities towards encoding packets.

Due to the lossy nature of wireless links, it is difficult to determine if packet losses are due to wireless-induced effects or from malicious discarding. Many prior efforts on detecting malicious packet drops rely on evidence collected via passive monitoring by neighbor nodes; however, they do not analyze the cause of packet losses. In this paper, we ask: (a) Given certain macroscopic parameters of the network (like traffic intensity and node density) what is the likelihood that evidence exists with respect to a transmission? and, (b) How can these parameters be used to perform a forensic analysis of the reason for the losses? Towards answering the above questions, we first build an analytical framework that computes the likelihood that evidence (we call this transmission evidence or TE for short) exists with respect to transmissions, in terms of a set of network parameters. We validate our analytical framework via both simulations as well as real-world experiments on two different wireless testbeds. The analytical framework is then used as a basis for a protocol within a forensic analyzer to assess the cause of packet losses and determine the likelihood of forwarding misbehaviors. Through simulations, we find that our assessments are close to the ground truth in all examined cases, with an average deviation of 2.3% from the ground truth and a worst case deviation of 15.0%.

Visible light communications (VLC) are gaining popularity and may provide an alternative means of communications in indoor settings. However, to date, there is very little research on the deployment or higher layer protocol design for VLC. In this paper, we first perform channel measurements using a physical layer testbed in the visible light band to understand its physical layer characteristics. Our measurements suggest that in order to increase data rates with VLC (1) the beam width of a communicating link can be shrunk, and (2) the transmission beam can be tuned to point towards the target recipient. We then perform Matlab simulations to verify that the human eye is able to accommodate the changes brought by shrinking a beam or by tuning the beam direction appropriately. As our main contribution, we then design a configuration framework for a VLC indoor local area network, which we call VICO; we leverage the above features towards achieving the highest throughput while maintaining fairness. VICO first tunes the beamwidths and pointing angles of the transmitters to configurations that provide the highest throughput for each client. It then tries to schedule transmissions while accounting for conflicts and the VLC PHY characteristics. Finally, it opportunistically tunes the idle LEDs to reinforce existing transmissions to increase throughput to the extent possible. We perform extensive simulations to demonstrate the effectiveness of VICO. We find that VICO provides as much as 5-fold increase in throughput compared to a simple scheduler that does not exploit the possible variations in beamwidth or beam-angle.

In this paper, we consider a variant of packet replay attacks wherein, an attacker simply replays overheard frames as they are, or with minor manipulations in the packet header; we refer to this as the copycat attack. When routers forward such replayed packets, the levels of congestion and interference increase in large portions of the network. Our experiments indicate that even a single attacker can degrade the route throughput by up to 61%. While simple to use techniques such as digitally signing every packet can stem the dissemination of such packets, they are resource intense. Thus, we design a lightweight detection and prevention system, COPS (for Copycat Online Prevention System), that intelligently uses a combination of digital signatures and Bloom filters to cope with the attack. With our system, the task of identifying and discarding replayed packets is distributed across a plurality of nodes on a route. We implement COPS on real hardware and perform experiments on our 42 node wireless testbed. Our measurements indicate that COPS achieves its objective; it can efficiently contain the effects of replayed packets to a local neighborhood without incurring high resource consumption penalties. Specifically, we show that COPS reduces the route throughput degradation by up to 66%.

As an alternative to radio-frequency (RF) communications, optical wireless communications (OWC) can support high data rates and low power operations while providing good jamming resistance. Our focus in this paper is on deep ultraviolet (UV) outdoor communications (UVOC) where solar blind and non-line-of-sight operations are attractive. Light beams from UV LED arrays serve as information carriers. In an abstract sense, this is similar to directional transmissions in RF; however, the PHY layer characteristics significantly differ due to atmospheric scattering. First, we perform extensive experiments on a UV testbed towards understanding signal propagation and the impact of the PHY on medium access. We find that UV propagation supports (a) fully duplex communications and (b) multiple data rate transmissions. Next, we propose a novel contention-based media access control (UVOC-MAC) protocol that inherently accounts for the UV PHY layer and fully exploits multi-fold spatial reuse opportunities. Evaluations via both simulations and analysis show that UVOC-MAC effectively mitigates collisions and achieves high throughput. In particular, up to a 4-fold increase in throughput and 50% reduction in collision are possible compared to a MAC protocol agnostic to the UV PHY properties.

The unlicensed 60 GHz band brings the promise of multi-gigabit data rates to support new applications such as high definition video over wireless links. Signal propagation in the 60 GHz band significantly differs from that in the traditionally used 2.4 and 5 GHz bands. The propagation and penetration losses in the 60 GHz band are much higher. Furthermore, the signals are often reflected in indoor settings. Previous physical layer studies show that the use of directional antennas can significantly help in coping with these effects. In this paper, we address the problem of neighbor discovery in the 60 GHz band. We account for not only discovery via direct line-of-sight paths, but also via reflected beams. To the best of our knowledge, none of the previous efforts on higher layer protocols for use with directional antennas account for reflections. We consider two approaches for neighbor discovery (a) direct discovery where each node explicitly discovers its neighbors and, (b) gossip-based discovery where nodes exchange information with regards to their already discovered neighbors. We develop analytical models to capture the performance of the two approaches and validate the models via simulations in indoor settings with obstacles that reflect the transmitted signals. As one might expect, the gossip based discovery incurs a lower neighbor-discovery latency than direct discovery. We examine the impact of system parameters such as varying beamwidth and node density. Our study provides insights on the right choice of system parameters for efficient neighbor discovery in the 60 GHz regime.