The AlphaGarden is an automated testbed for indoor polyculture farming which combines a first-order plant simulator, a gantry robot, a seed planting algorithm, plant phenotyping and tracking algorithms, irrigation sensors and algorithms, and custom pruning tools and algorithms. In this paper, we systematically compare the performance of the AlphaGarden to professional horticulturalists on the staff of the UC Berkeley Oxford Tract Greenhouse. The humans and the machine tend side-by-side polyculture gardens with the same seed arrangement. We compare performance in terms of canopy coverage, plant diversity, and water consumption. Results from two 60-day cycles suggest that the automated AlphaGarden performs comparably to professional horticulturalists in terms of coverage and diversity, and reduces water consumption by as much as 44%. Code, videos, and datasets are available at https//sites.google.com/berkeley.edulsystematiccomparison

Recent research indicates that multi-hop wireless networks can suffer from extreme imbalances in the throughput achieved by simultaneous competing flows. We address this problem by designing a practical distributed algorithm to compute a time-slot based schedule that provides end-to-end max-min fairness. Our system uses randomized priorities based on local weights to arbitrate access between nodes that directly compete with each other (we call this weighted slot allocation or WSA). The local weights are in turn computed by a higher layer called end-to-end fairness using local weights (EFLoW). EFLoW implements an additive-increase multiplicative-decrease (AIMD) algorithm that can automatically adapt to changes in traffic demands and network conditions. In each iteration, EFLoW only uses state obtained from within a given node's contention region. We have implemented WSA and EFLoW in both a simulator and a real system by using the overlay MAC layer (OML). Unlike previous work on end-to-end fairness, our approach does not use a centralized coordinator and works for traffic patterns with any number of sources and sinks. Also, since we compute both the fair allocation and a schedule to achieve it, we do not make any assumptions about the efficiency of carrier-sense (CS) based MACs - this is very important in the light of recent work which shows that current CS-based MACs can be very unfair even when all nodes are limited to sending at their fair rate. Our results show that WSA and EFLoW can prevent starvation of flows and improve fairness without sacrificing efficiency for a wide variety of traffic patterns.

The widespread availability of 802.11-based hardware has made it the premier choice of both researchers and practitioners for developing new wireless networks and applications. However, the ever increasing set of demands posed by these applications is stretching the 802.11 MAC protocol beyond its intended capabilities. For example, 802.11 provides no control over allocation of resources, and the default allocation policy is ill-suited for heterogeneous environments and multi-hop networks. Fairness problems are further exacerbated in multi-hop networks due to link asymmetry and hidden terminals. In this paper, we take a first step towards addressing these problems without replacing the MAC layer by presenting the design and the implementation of an Overlay MAC Layer (OML), that works on top of the 802.11 MAC layer. OML uses loosely-synchronized clocks to divide the time in to equal size slots, and employs a distributed algorithm to allocate these slots among competing nodes. We have implemented OML in both a simulator and on a wireless testbed using the Click modular router. Our evaluation shows that OML can not only provide better flexibility but also improve the fairness, throughput and predictability of 802.11 networks.

Effective network troubleshooting is critical for maintaining efficient and reliable network operation. Troubleshooting is especially challenging in multihop wireless networks because the behavior of such networks depends on complicated interactions between many unpredictable factors such as RF noise, signal propagation, node interference, and traffic flows. In this paper we propose a new direction for research on fault diagnosis in wireless networks. Specifically, we present a diagnostic system that employs trace-driven simulations to detect faults and perform root cause analysis. We apply this approach to diagnose performance problems caused by packet dropping, link congestion, external noise, and MAC misbehavior. In a 25 node multihop wireless network, we are able to diagnose over 10 simultaneous faults of multiple types with more than 80% coverage. Our framework is general enough for a wide variety of wireless and wired networks.

For many years, scalable routing for wireless communication systems was a compelling but elusive goal. Recently, several routing algorithms that exploit geographic information (e.g. GPSR) have been proposed to achieve this goal. These algorithms refer to nodes by their location, not address, and use those coordinates to route greedily, when possible, towards the destination. However, there are many situations where location information is not available at the nodes, and so geographic methods cannot be used. In this paper we define a scalable coordinate-based routing algorithm that does not rely on location information, and thus can be used in a wide variety of ad hoc and sensornet environments.