Strategyproof Computing: Systems Infrastructures for Self-Interested Parties

The widespread deployment of high-speed internet access is ushering in a new era of distributed computing, in which parties both contribute to a global pool of shared resources and access the pooled resources to support their own computing needs. We argue that system designers must explicitly address the self-interest of individual parties if these next-generation computing systems are to flourish. We propose strategyproof computing, a vision for an open computing infrastructure in which resource allocation and negotiation schemes are incentive-compatible, and individual parties can treat other resources as their own. In this paper we outline key guiding principles for the vision of strategyproof computing, define the strategyproof computing paradigm, and lay out a systems-related research agenda.Engineering and Applied Science

Virtual Worlds: Fast and Strategyproof Auctions for Dynamic Resource Allocation

We consider the problem of designing fast and strategyproof exchanges for dynamic resource allocation problems in distributed systems. The exchange is implemented as a sequence of auctions, with dynamically arriving requests from agents matched with each auction. Each auction is associated with some consignment of the resources from a single seller. We provide a simple Virtual Worlds (VW) construction, that extends a fast and strategyproof mechanism for a single auction to apply to this sequence-of-auctions setting. Rather than match each buyer with a single auction, the VW mechanism allows buyers to be considered for multiple auctions while retaining strategyproofness.Engineering and Applied Science

Provenance-Aware Sensor Data Storage

Sensor network data has both historical and realtime value. Making historical sensor data useful, in particular, requires storage, naming, and indexing. Sensor data presents new challenges in these areas. Such data is location-specific but also distributed; it is collected in a particular physical location and may be most useful there, but it has additional value when combined with other sensor data collections in a larger distributed system. Thus, arranging location-sensitive peer-to-peer storage is one challenge. Sensor data sets do not have obvious names, so naming them in a globally useful fashion is another challenge. The last challenge arises from the need to index these sensor data sets to make them searchable. The key to sensor data identity is provenance, the full history or lineage of the data. We show how provenance addresses the naming and indexing issues and then present a research agenda for constructing distributed, indexed repositories of sensor data.Engineering and Applied Science

Provenance-Aware Sensor Data Storage

Sensor network data has both historical and realtime value. Making historical sensor data useful, in particular, requires storage, naming, and indexing. Sensor data presents new challenges in these areas. Such data is location-specific but also distributed; it is collected in a particular physical location and may be most useful there, but it has additional value when combined with other sensor data collections in a larger distributed system. Thus, arranging location-sensitive peer-to-peer storage is one challenge. Sensor data sets do not have obvious names, so naming them in a globally useful fashion is another challenge. The last challenge arises from the need to index these sensor data sets to make them searchable. The key to sensor data identity is provenance, the full history or lineage of the data. We show how provenance addresses the naming and indexing issues and then present a research agenda for constructing distributed, indexed repositories of sensor data.Engineering and Applied Science

Why Markets Could (But Don't Currently) Solve Resource Allocation Problems in Systems

Using market mechanisms for resource allocation in distributed systems is not a new idea, nor is it one that has caught on in practice or with a large body of computer science research. Yet, projects that use markets for distributed resource allocation recur every few years [1, 2, 3], and a new generation of research is exploring market-based resource allocation mechanisms [4, 5, 6, 7, 8] for distributed environments such as Planetlab, Netbed, and computational grids. This paper has three goals. The first goal is to explore why markets can be appropriate to use for allocation, when simpler allocation mechanisms exist. The second goal is to demonstrate why a new look at markets for allocation could be timely, and not a re-hash of previous research. The third goal is to point out some of the thorny problems inherent in market deployment and to suggest action items both for market designers and for the greater research community. We are optimistic about the power of market design, but we also believe that key challenges exist for a markets/systems integration that must be overcome for market-based computer resource allocation systems to succeed.Engineering and Applied Science

Two Auction-Based Resource Allocation Environments: Design and Experience

Many computer systems have reached the point where the goal of resource allocation is no longer to maximize utilization; instead, when demand exceeds supply and not all needs can be met, one needs a policy to guide resource allocation decisions. One natural policy is to seek efficient usage, which allocates resources to the set of users who have the highest utility for the use of the resources. Researchers have frequently proposed market-based mechanisms to provide such a goal-oriented way to allocate resources among competing interests while maximizing overall utility of the users.Engineering and Applied Science

Mirage: A Microeconomic Resource Allocation System for Sensornet Testbeds

In this paper, we argue that a microeconomic resource allocation scheme, specifically the combinatorial auction, is well suited to testbed resource management. To demonstrate this, we present the Mirage resource allocation system. In Mirage, testbed resources are allocated using a repeated combinatorial auction within a closed virtual currency environment. Users compete for testbed resources by submitting bids which specify resource combinations of interest in space/time (e.g., "any 32 MICA2 motes for 8 hours anytime in the next three days") along with a maximum value amount the user is willing to pay. A combinatorial auction is then periodically run to determine the winning bids based on supply and demand while maximizing aggregate utility delivered to users. We have implemented a fully functional and secure prototype of Mirage and have been operating it in daily use for approximately four months on Intel Research Berkeley's 148-mote sensornet testbed.Engineering and Applied Science

Egg: An Extensible and Economics-Inspired Open Grid Computing Platform

The Egg project provides a vision and implementation of how heterogeneous computational requirements will be supported within a single grid and a compelling reason to explain why computational grids will thrive. Environment computing, which allows a user to specify properties that a compute environment must satisfy in order to support the user’s computation, provides a how. Economic principles, allowing resource owners, users, and other stakeholders to make value and policy statements, provides a why. The Egg project introduces a language for defining software environments (egg shell), a general type for grid objects (the cache), and a currency (the egg). The Egg platform resembles an economically driven Internetwide Unix system with egg shell playing the role of a scripting language and caches playing the role of a global file system, including an initial collection of devices.Engineering and Applied Science

Whole-exome resequencing distinguishes cystic kidney diseases from phenocopies in renal ciliopathies

Rare single-gene disorders cause chronic disease. However, half of the 6,000 recessive single gene causes of disease are still unknown. Because recessive disease genes can illuminate, at least in part, disease pathomechanism, their identification offers direct opportunities for improved clinical management and potentially treatment. Rare diseases comprise the majority of chronic kidney disease (CKD) in children but are notoriously difficult to diagnose. Whole exome resequencing facilitates identification of recessive disease genes. However, its utility is impeded by the large number of genetic variants detected. We here overcome this limitation by combining homozygosity mapping with whole exome resequencing in 10 sib pairs with a nephronophthisis-related ciliopathy, which represents the most frequent genetic cause of CKD in the first three decades of life. In 7 of 10 sib-ships with a histologic or ultrasonographic diagnosis of nephronophthisis-related ciliopathy we detect the causative gene. In six sib-ships we identify mutations of known nephronophthisis-related ciliopathy genes, while in two additional sib-ships we found mutations in the known CKD-causing genes SLC4A1 and AGXT as phenocopies of nephronophthisis-related ciliopathy. Thus whole exome resequencing establishes an efficient, non-invasive approach towards early detection and causation-based diagnosis of rare kidney diseases. This approach can be extended to other rare recessive disorders, thereby providing accurate diagnosis and facilitating the study of disease mechanisms

FAT1 mutations cause a glomerulotubular nephropathy

Steroid-resistant nephrotic syndrome (SRNS) causes 15% of chronic kidney disease (CKD). Here we show that recessive mutations in FAT1 cause a distinct renal disease entity in four families with a combination of SRNS, tubular ectasia, haematuria and facultative neurological involvement. Loss of FAT1 results in decreased cell adhesion and migration in fibroblasts and podocytes and the decreased migration is partially reversed by a RAC1/CDC42 activator. Podocyte-specific deletion of Fat1 in mice induces abnormal glomerular filtration barrier development, leading to podocyte foot process effacement. Knockdown of Fat1 in renal tubular cells reduces migration, decreases active RAC1 and CDC42, and induces defects in lumen formation. Knockdown of fat1 in zebrafish causes pronephric cysts, which is partially rescued by RAC1/CDC42 activators, confirming a role of the two small GTPases in the pathogenesis. These findings provide new insights into the pathogenesis of SRNS and tubulopathy, linking FAT1 and RAC1/CDC42 to podocyte and tubular cell function