From mboxrd@z Thu Jan 1 00:00:00 1970 Return-Path: Received: from mail2.tohojo.dk (mail2.tohojo.dk [77.235.48.147]) (using TLSv1 with cipher DHE-RSA-AES256-SHA (256/256 bits)) (Client did not present a certificate) by huchra.bufferbloat.net (Postfix) with ESMTPS id 2504921F22E for ; Mon, 27 Apr 2015 02:20:43 -0700 (PDT) X-Virus-Scanned: amavisd-new at mail2.tohojo.dk Sender: toke@toke.dk DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/relaxed; d=toke.dk; s=201310; t=1430126436; bh=k2r6ZdN3aLQjaAqE4brZnmtSSoLQTPh4gessBYZvRhk=; h=From:To:Cc:Subject:References:Date:In-Reply-To; b=QDdBYsAlOzhSuxBpZZ73K2ECaezirtS69KKCw7bLUfC2dWxNB9PFkiCh75Tnf4JjQ VA/bqF1whxF52ROoWVHCmAvWqtO/o6tylumta3S9sB/0EyOCM9SdXE34eHtQvCuqIQ svcSuH/RhpuAVc7IOHv55JEKg3GRDtBpBeL7RX68= Received: by alrua-kau.kau.toke.dk (Postfix, from userid 1000) id 720BEC40134; Mon, 27 Apr 2015 11:20:35 +0200 (CEST) From: =?utf-8?Q?Toke_H=C3=B8iland-J=C3=B8rgensen?= To: Paolo Valente References: <3E2406CD-0938-4C1F-B171-247CBB5E4C7D@unimore.it> Date: Mon, 27 Apr 2015 11:20:35 +0200 In-Reply-To: <3E2406CD-0938-4C1F-B171-247CBB5E4C7D@unimore.it> (Paolo Valente's message of "Mon, 27 Apr 2015 10:59:48 +0200") X-Clacks-Overhead: GNU Terry Pratchett Message-ID: <87zj5u2aho.fsf@toke.dk> MIME-Version: 1.0 Content-Type: text/plain Cc: bloat Subject: Re: [Bloat] bufferbloat effects on throughput X-BeenThere: bloat@lists.bufferbloat.net X-Mailman-Version: 2.1.13 Precedence: list List-Id: General list for discussing Bufferbloat List-Unsubscribe: , List-Archive: List-Post: List-Help: List-Subscribe: , X-List-Received-Date: Mon, 27 Apr 2015 09:21:12 -0000 Paolo Valente writes: > If there are, could anyone please point me to further reading on these > aspects? Bufferbloat can definitely adversely affect throughput in some cases. Mainly because it causes throughput to oscillate: when the queue fills, a lot of data can be dropped at once, causing throughput to drop, which takes a while to recover. This can degrade aggregate throughput. Having smart queueing smoothes out the traffic, so the oscillations are lower and average throughput thus better. The effect is most visible when you have several flows sharing a link: when the (FIFO) queue fills, they will tend to all experience drops at once, and so all slow down. -Toke