top-k queries for multi-category rfid systems This paper studies the practically important problem of top-k queries, which is to find the top k largest categories and their corresponding sizes. In this paper, we propose a Top-k Query (TKQ) protocol and a technique that we call Segmented Perfect Hashing (SPH) for optimizing TKQ.
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This paper studies the practically important problem of top-k queries, which is to find the top k largest categories and their corresponding sizes. In this paper, we propose a Top-k Query (TKQ) protocol and a technique that we call Segmented Perfect Hashing (SPH) for optimizing TKQ.We define the Multi-category RFID Top-k Query problem as: given a set of tags that can be classified into ` categories C1; C2; :::; C`, error thresholds "; (0; 1], and reliability. a multi .
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ABSTRACT. This paper studies the practically important problem of top-k queries, which is to find the top k largest categories and their corresponding sizes. In this paper, we propose a Top-k .pA blocker tag is an RFID device that is preconfigured with a set of known RFID tag IDs, which we call blocking IDs. The blocker tag behaves as if all tags with its blocking IDs are present. What . This paper proposes a Top-k Query (TKQ) protocol and a technique that it is called Segmented Perfect Hashing (SPH) for optimizing TKQ, which achieves a 2.6~7x faster speed .
This paper studies the practically important problem of top-k queries, which is to find the top k largest categories and their corresponding sizes. In this paper, we propose a Top-k Query (TKQ) protocol and a technique that we call Segmented Perfect Hashing (SPH) for optimizing TKQ.We define the Multi-category RFID Top-k Query problem as: given a set of tags that can be classified into ` categories C1; C2; :::; C`, error thresholds "; (0; 1], and reliability. a multi-category RFID top-k query 2 requirements ; [0; 1), scheme outputs a set of 2. category in.
ABSTRACT. This paper studies the practically important problem of top-k queries, which is to find the top k largest categories and their corresponding sizes. In this paper, we propose a Top-k Query (TKQ) protocol and a technique that we call Segmented Perfect Hashing (SPH) for optimizing TKQ.pA blocker tag is an RFID device that is preconfigured with a set of known RFID tag IDs, which we call blocking IDs. The blocker tag behaves as if all tags with its blocking IDs are present. What is the blocker tags? This paper proposes a Top-k Query (TKQ) protocol and a technique that it is called Segmented Perfect Hashing (SPH) for optimizing TKQ, which achieves a 2.6~7x faster speed than the existing protocols.
Ever-increasing research efforts have been dedicated to radio frequency identification (RFID) systems, such as finding top-k, elephant groups, and missing-tag detection.In this paper, we define a new class of queries, the top-k multiple-type integrated query (simply, top-k MULTI query). It deals with multiple data types and finds the information in the order of relevance between the query and the object. For categorized RFID systems, this paper studies the practically important problem of top-k queries, which is to find the top-k smallest and (or) the top-k largest categories, as well as the sizes of such categories.For categorized RFID systems, this paper studies the practically important problem of top-k queries, which is to find the top-k smallest and or the top-k largest categories, as well as the sizes of.
For categorized RFID systems, this paper studies the practically important problem of top- k queries, which is to find the top- k smallest and (or) the top- k largest categories, as well as the sizes of such categories.This paper studies the practically important problem of top-k queries, which is to find the top k largest categories and their corresponding sizes. In this paper, we propose a Top-k Query (TKQ) protocol and a technique that we call Segmented Perfect Hashing (SPH) for optimizing TKQ.We define the Multi-category RFID Top-k Query problem as: given a set of tags that can be classified into ` categories C1; C2; :::; C`, error thresholds "; (0; 1], and reliability. a multi-category RFID top-k query 2 requirements ; [0; 1), scheme outputs a set of 2. category in.ABSTRACT. This paper studies the practically important problem of top-k queries, which is to find the top k largest categories and their corresponding sizes. In this paper, we propose a Top-k Query (TKQ) protocol and a technique that we call Segmented Perfect Hashing (SPH) for optimizing TKQ.
pA blocker tag is an RFID device that is preconfigured with a set of known RFID tag IDs, which we call blocking IDs. The blocker tag behaves as if all tags with its blocking IDs are present. What is the blocker tags? This paper proposes a Top-k Query (TKQ) protocol and a technique that it is called Segmented Perfect Hashing (SPH) for optimizing TKQ, which achieves a 2.6~7x faster speed than the existing protocols. Ever-increasing research efforts have been dedicated to radio frequency identification (RFID) systems, such as finding top-k, elephant groups, and missing-tag detection.
In this paper, we define a new class of queries, the top-k multiple-type integrated query (simply, top-k MULTI query). It deals with multiple data types and finds the information in the order of relevance between the query and the object. For categorized RFID systems, this paper studies the practically important problem of top-k queries, which is to find the top-k smallest and (or) the top-k largest categories, as well as the sizes of such categories.For categorized RFID systems, this paper studies the practically important problem of top-k queries, which is to find the top-k smallest and or the top-k largest categories, as well as the sizes of.
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Available from iOS 11.0 – learn more in my book Advanced iOS: Volume Two. .“There’s an app for that” will soon become “Ah, there’s an app clip for this!” If you don’t know what App Clips are, let me bring you up to speed. App Clips are basically a lighter version of an app dedicated to just a single task, and they can be discovered at just the right moment. Discovering app clips in the real-world . See more
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