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Bloomier filters: A second look
 Algorithms  ESA 2008, 16th Annual European Symposium
"... Abstract. A Bloom filter is a space efficient structure for storing static sets, where the space efficiency is gained at the expense of a small probability of falsepositives. A Bloomier filter generalizes a Bloom filter to compactly store a function with a static support. In this article we give a ..."
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Abstract. A Bloom filter is a space efficient structure for storing static sets, where the space efficiency is gained at the expense of a small probability of falsepositives. A Bloomier filter generalizes a Bloom filter to compactly store a function with a static support. In this article we give a simple construction of a Bloomier filter. The construction is linear in space and requires constant time to evaluate. The creation of our Bloomier filter takes linear time which is faster than the existing construction. We show how one can improve the space utilization further at the cost of increasing the time for creating the data structure. 1
HashBased Techniques for HighSpeed Packet Processing
"... Abstract Hashing is an extremely useful technique for a variety of highspeed packetprocessing applications in routers. In this chapter, we survey much of the recent work in this area, paying particular attention to the interaction between theoretical and applied research. We assume very little bac ..."
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Abstract Hashing is an extremely useful technique for a variety of highspeed packetprocessing applications in routers. In this chapter, we survey much of the recent work in this area, paying particular attention to the interaction between theoretical and applied research. We assume very little background in either the theory or applications of hashing, reviewing the fundamentals as necessary. 1
Simple Summaries for Hashing with Multiple Choices
"... In a multiplechoice hashing scheme, each item is stored in one of d> = 2 possible hash tablebuckets. The availability of these multiple choices allows for a substantial reduction in the maximum load of the buckets. However, a lookup may now require examining each of the d locations. Forapplicat ..."
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In a multiplechoice hashing scheme, each item is stored in one of d> = 2 possible hash tablebuckets. The availability of these multiple choices allows for a substantial reduction in the maximum load of the buckets. However, a lookup may now require examining each of the d locations. Forapplications where this cost is undesirable, Song et al. propose keeping a summary that allows one to determine which of the d locations is appropriate for each item, where the summary may allowfalse positives for items not in hash table. We propose alternative, simple constructions of such summaries that use less space for both the summary and the underlying hash table. Moreover, ourconstructions are easily analyzable and tunable.
COPS: An Efficient Content Oriented Publish/Subscribe System
"... ContentCentric Networks (CCN) provide substantial flexibility for users to obtain information without regard to the source of the information or its current location. Publish/ subscribe (pub/sub) systems have gained popularity in society to provide the convenience of removing the temporal dependenc ..."
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ContentCentric Networks (CCN) provide substantial flexibility for users to obtain information without regard to the source of the information or its current location. Publish/ subscribe (pub/sub) systems have gained popularity in society to provide the convenience of removing the temporal dependency of the user having to indicate an interest each time he or she wants to receive a particular piece of related information. Currently, on the Internet, such pub/sub systems have been built on top of an IPbased network with the additional responsibility placed on the endsystems and servers to do the work of getting a piece of information to interested recipients. We propose ContentOriented Pub/Sub system (COPS) to achieve an efficient pub/sub capability for CCN. COPS enhances the heretofore inherently pullbased CCN architectures proposed by integrating push based multicast at the contentcentric layer. We emulate an application that is particularly emblematic of a pub/sub environment—Twitter—but one where subscribers are interested in content (e.g., identified by keywords), rather than tweets from a particular individual. Using tracedriven simulation, we demonstrate that our architecture can achieve a scalable and efficient pub/sub content centric network. The simulator is parameterized using the results of
Buffered Bloom filters on solid state storage
 In First Intl. Workshop on Accelerating Data Management Systems Using Modern Processor and Storage Architectures (ADMS*10
, 2010
"... Bloom Filters are widely used in many applications including database management systems. With a certain allowable error rate, this data structure provides an efficient solution for membership queries. The error rate is inversely proportional to the size of the Bloom filter. Currently, Bloom filters ..."
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Bloom Filters are widely used in many applications including database management systems. With a certain allowable error rate, this data structure provides an efficient solution for membership queries. The error rate is inversely proportional to the size of the Bloom filter. Currently, Bloom filters are stored in main memory because the low locality of operations makes them impractical on secondary storage. In multiuser database management systems, where there is a high contention for the shared memory heap, the limited memory available for allocating a Bloom filter may cause a high rate of false positives. In this paper we are proposing a technique to reduce the memory requirement for Bloom filters with the help of solid state storage devices (SSD). By using a limited memory space for buffering the read/write requests, we can afford a larger SSD space for the actual Bloom filter bit vector. In our experiments we show that with significantly less memory requirement and fewer hash functions the proposed technique reduces the false positive rate effectively. In addition, the proposed data structure runs faster than the traditional Bloom filters by grouping the inserted records with respect to their locality on the filter. 1.
Backyard Cuckoo Hashing: Constant WorstCase Operations with a Succinct Representation
, 2010
"... The performance of a dynamic dictionary is measured mainly by its update time, lookup time, and space consumption. In terms of update time and lookup time there are known constructions that guarantee constanttime operations in the worst case with high probability, and in terms of space consumption ..."
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The performance of a dynamic dictionary is measured mainly by its update time, lookup time, and space consumption. In terms of update time and lookup time there are known constructions that guarantee constanttime operations in the worst case with high probability, and in terms of space consumption there are known constructions that use essentially optimal space. In this paper we settle two fundamental open problems: • We construct the first dynamic dictionary that enjoys the best of both worlds: we present a twolevel variant of cuckoo hashing that stores n elements using (1+ϵ)n memory words, and guarantees constanttime operations in the worst case with high probability. Specifically, for any ϵ = Ω((log log n / log n) 1/2) and for any sequence of polynomially many operations, with high probability over the randomness of the initialization phase, all operations are performed in constant time which is independent of ϵ. The construction is based on augmenting cuckoo hashing with a “backyard ” that handles a large fraction of the elements, together with a deamortized perfect hashing scheme for eliminating the dependency on ϵ.
Share with thy neighbors
 in Multimedia Computing and Networking (MMCN 2007
, 2007
"... Peer to peer (P2P) systems are traditionally designed to scale to a large number of nodes. However, we focus on scenarios where the sharing is effected only among neighbors. Localized sharing is particularly attractive in scenarios where wide area network connectivity is undesirable, expensive or un ..."
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Peer to peer (P2P) systems are traditionally designed to scale to a large number of nodes. However, we focus on scenarios where the sharing is effected only among neighbors. Localized sharing is particularly attractive in scenarios where wide area network connectivity is undesirable, expensive or unavailable. On the other hand, local neighbors may not offer the wide variety of objects possible in a much larger system. The goal of this paper is to investigate a P2P system that shares contents with its neighbors. We analyze the sharing behavior of Apple iTunes users in an University setting. iTunes restricts the sharing of audio and video objects to peers within the same LAN subnetwork. We show that users are already making a significant amount of content available for local sharing. We show that these systems are not appropriate for applications that require access to a specific object. We argue that mechanisms that allow the user to specify classes of interesting objects are better suited for these systems. Mechanisms such as bloom filters can allow each peer to summarize the contents available in the neighborhood, reducing network search overhead. This research can form the basis for future storage systems that utilize the shared storage available in neighbors and build a probabilistic storage for local consumption.
Simple Summaries for Hashing with Choices
 IEEE/ACM TRANSACTIONS ON NETWORKING
, 2008
"... In a multiplechoice hashing scheme, each item is stored in one of P possible hash table buckets. The availability of these multiple choices allows for a substantial reduction in the maximum load of the buckets. However, a lookup may now require examining each of the locations. For applications whe ..."
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In a multiplechoice hashing scheme, each item is stored in one of P possible hash table buckets. The availability of these multiple choices allows for a substantial reduction in the maximum load of the buckets. However, a lookup may now require examining each of the locations. For applications where this cost is undesirable, Song et al. propose keeping a summary that allows one to determine which of the locations is appropriate for each item, where the summary may allow false positives for items not in hash table. We propose alternative, simple constructions of such summaries that use less space for both the summary and the underlying hash table. Moreover, our constructions are easily analyzable and tunable.
Weighted Bloom Filter
"... A Bloom filter is a simple randomized data structure that answers membership query with no false negative and a small false positive probability. It is an elegant data compression technique for membership information and has broad applications. In this paper, we generalize the traditional Bloom fi ..."
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A Bloom filter is a simple randomized data structure that answers membership query with no false negative and a small false positive probability. It is an elegant data compression technique for membership information and has broad applications. In this paper, we generalize the traditional Bloom filter to Weighted Bloom Filter, which incorporates the information on the query frequencies and the membership likelihood of the elements into its optimal design. It has been widely observed that in many applications, some popular elements are queried much more often than the others. The traditional Bloom filter for data sets with irregular query patterns and nonuniform membership likelihood can be further optimized. We derive the optimal configuration of the Bloom filter with queryfrequency and membershiplikelihood information, and show that the adapted Bloom filter always outperforms the traditional Bloom filter. Under reasonable frequency models such as the step distribution or the Zipf’s distribution, the improvement of the false positive probability of the weighted Bloom filter over that of the traditional Bloom filter has been evaluated by simulations.